Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
DETAILED ACTION
The following NON-FINAL Office Action is in response to communication filed on 1/6/2026.
Continued Examination under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on MM/DD/YYYY has been entered.
Status of Claims
Claims 1-21 are currently pending of which:
Claims 1, 12 are currently amended.
Claims 1-21 are currently under examination and have been rejected as follows.
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Response to Amendment
New rejection is applied under 35 USC 112 as necessitated by the amendments.
The previously pending rejections under 35 USC 101 will be maintained. The 101 rejection is updated in view of the amendments.
The previous pending rejection under 35 USC 103 will be maintained. The 103 rejection is updated in view of the amendments.
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Response to Arguments
Regarding Applicant’s remarks pertaining to 35 USC 101:
Step 2A Prong 1:
Applicant argues starting on page 9 of remarks 1/6/2026:
“This specific combination of steps-validation, dual-list sorting, and greedy matching-is a specific technological process for handling data records, not a ‘fundamental economic practice’ or ‘managing personal behavior.’ In Enfish, LLC v. Microsoft Corp., the Federal Circuit clarified that claims directed to an improvement in the functioning of a computer (e.g., a specific data structure or algorithm) are not abstract. Similarly here, the claims recite a specific algorithm for optimizing data allocation (shifts to days) that goes beyond the generic concept of ‘scheduling.’ Therefore, the claims do not recite an abstract idea under Step 2A, Prong 1.”
Examiner respectfully disagrees. “Managing Personal Behavior” notwithstanding, rather than “fundamental economic principles”, Examiner relies upon a separate subgrouping of Certain Methods of Organizing Human Activity: “commercial or legal interactions”. Examiner re-asserts that collecting shift history data, collecting worker preferences, generating schedule options based on scoring functions for workers, and creating worker schedules fall within agreements in the form of contracts and business relations as they pertain to commercial or legal interactions, or managing personal behavior or relationships or interactions between people, each within the larger abstract grouping of Certain Methods of Organizing Human Activity (MPEP 2106.04(a)(2) II). Applicant specification at ¶ [0003] states “As will be appreciated, the suggested schedule generation provides for efficient schedule generation. The techniques described herein improve the consistency and accuracy of schedules. The techniques described herein also improve the overall employee satisfaction with their schedule by satisfying the employee preferences and facilitating fast and efficient changes to schedules.” Computer technology is used, but the problem addressed by the technical solution is entrepreneurial. Accordingly, the claims recite an abstract idea.
Step 2A Prong 2:
Applicant argues beginning on page 9 of remarks 1/6/2026:
“Even if the claims were viewed as reciting an abstract idea, they integrate the concept into a practical application. The amended claims recite a specific improvement to the functioning of the computer system itself. Reduced Computational Load: By reciting the step of ‘validating ... to generate a set of validated open shifts’ prior to the scoring step, the claimed invention ensures that the resource-intensive scoring function is only applied to valid data. This avoids the processing of invalid shifts, conserving processor cycles and memory (supported by Para [0003]
regarding reducing ‘processor load’). Specific Rules: The claims impose meaningful limits by requiring the calculation of a ‘day rank… based on a workload measure’ and matching based on that rank. This is not a generic ‘apply it on a computer’ instruction, but a specific rule set for automating the task, analogous to McRO, Inc.”.
Examiner respectfully disagrees. Mere automation of manual processes alone is not sufficient to demonstrate an improvement in computer-functionality (see MPEP 2106.05(a) I (iii)). Applicant specification ¶ [0019-0020] states “…Manual schedule creation requires an employee to build their schedule by hand, picking open shifts for each day. Manual methods, while providing an ability to accommodate employee selections, are a tedious, time-consuming, repetitive, and error-prone process. The techniques described herein introduce an auto-generation of an employee (also referred to as a user herein) schedule.”
Despite the similarity with McRO in terms of applying a specific rule set for automating a task, the McRO appellate decision finding the subject matter eligible rested upon the claims not being directed to an abstract idea in the first place, rather than assessing the practical application of an abstract idea or providing significantly more via the automation.
Examiner notes the claims as amended do not introduce any new additional computer-based elements. The original computer-based elements include “computer”, “system”, “server computer”, “processor”, “memory”, “database”, and “user interface”. The functions of these additional elements include examples such as “query a schedule database”, “receive schedule preferences”, “assemble a first set of user shift features”, “select a score function”, “compute… an open shift score”, “sort the set of open shifts”, “assemble a first schedule”, “generate… a depiction of the first schedule”, and now as amended, “selecting… the score function… is further based on a historical success of the score function resulting in schedule selection”. As previously asserted, the additional elements are recited at high level of generality because they perform functions searching for, scoring, calculating mathematically, ranking, assembling, and presenting data, but additional technological details of how these functions are carried out which would separate them from conventional technology solutions are insufficient in the claims. Thus, these functions can be viewed as not meaningfully different than a business method or mathematical algorithm being applied on a general-purpose computer as tested per MPEP 2106.05(f)(2)(i).
Step 2B:
Applicant argues beginning on page 9 of remarks 1/6/2026:
“Finally, even if the claims failed Step 2A, they possess an inventive concept under Step
2B. The ordered combination of: (1) querying historical features to dynamically select a scoring function, (2) pre-validating the dataset, (3) ranking days by workload, and (4) matching the sorted
lists, amounts to significantly more than the abstract idea. The prior art (discussed below) does not teach this specific combination. Thompson teaches routing based on travel time, not ranking days by workload. The claimed combination represents a non-conventional arrangement of computing steps that solves the specific problem of efficiently generating a self-schedule recommendation, which is not a well-understood, routine, or conventional activity”
Examiner respectfully disagrees. As previously asserted, the additional elements are recited at high level of generality because they perform functions searching for, scoring, calculating, ranking, assembling, and presenting data, etc. Applicant specification describes the conventionality of the additional elements, among others, at ¶ [0095]: “the depicted and/or described elements, the functions thereof, and/or arrangements of these, may be implemented on machines, such as through computer executable transitory and/or non-transitory media having a processor capable of executing program instructions stored thereon, and/or as logical circuits or hardware arrangements”; and ¶ [0096]: “The computer executable code may be created using a structured programming language such as C, an object oriented programming language such as C++, or any other high level or low-level programming language (including assembly languages, hardware description languages, and database programming languages and technologies) that may be stored, compiled or interpreted to run on one of the above devices, as well as heterogeneous combinations of processors, processor architectures, or combinations of different hardware and computer readable instructions, or any other machine capable of executing program instructions”. Additional technological details of how the claimed functions are carried out which would separate them from conventional technology are insufficient in the claims.
Thus, the rejection under 35 USC 101 is maintained. The 101 rejection is updated in view of the amendments.
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Regarding Applicant’s remarks pertaining to 35 USC 103:
A. Applicant argues on page 11 of remarks 1/6/2026:
“First, Thompson fails to disclose ‘validating, by the processor, the set of open shifts against applicable scheduling rules to generate a set of validated open shifts,’ as recited in amended claims 1 and 12. In contrast, Thompson ranks all available jobs to find an optimal route. It does not teach the specific step of validating shifts against rules to generate a separate ‘set of validated open shifts’ prior to scoring, as recited in amended claims 1 and 12.
Examiner respectfully finds Applicant’s argument unpersuasive. Although neither Thompson does not teach or suggest the validation limitation, previously presented reference Balusani discloses, within the broadest reasonable interpretation, narrowing valid open shifts as a subset of open shifts at Fig. 14 Step 712: “Assign selected week to employee a as new week 1, decrease available allotment for new week”; Fig. 15 Step 808: “Scan preference #1 of employee #10083 requesting change of week #11 to week #8”; Step 810: “Assign week #8 to employee #10083 as new week 1, decrease available allotment for week #8”.
Applicant continues on page 11 of remarks 1/6/2026:
“Second, Thompson fails to disclose ‘calculating, by the processor, a day rank for each day of the set of days based on a workload measure; sorting, by the processor, the set of days based on the day rank to generate an ordered list of days; ... sorting, by the processor, the set of validated open shifts based on the open shift scores to generate an ordered list of open shifts and the ordered list of days, wherein assembling the schedule comprises matching a first open shift from the ordered list of open shifts to a first day from the ordered list of days,’ as recited by amended claims 1 and 12. In contrast, Thompson generates a schedule based on time slots within a day (Para [0008]). It does not teach calculating a day rank for a set of days based on a workload measure, sorting the days, and then matching a top-ranked shift to a top-ranked day. Thompson's logic is ‘Route Optimization’ (filling a sequence based on location), whereas the claimed invention is ‘Priority Allocation’ (filling high-demand days first based on workload).”
Examiner respectfully finds Applicant’s argument unpersuasive. Although Thompson at ¶ [0008] points to one example, further support for Thompson teaching the limitation is found at ¶ [0057], [0062], [0095]. Examiner applies broadest reasonable interpretation of “day” rank as interchangeable with “job” rank, as is common in assigning shifts in a workforce. Although location is one factor in Thompson’s scheduling method, current workload is also a factor, among others. Additional details and citations are included in the 103 rejection section below.
B1. Applicant argues on page 12 of remarks 1/6/2026:
“…deSilva does not teach calculating a day rank based on a workload measure and sorting a set of days to generate a schedule from scratch. de Silva's constraints are used to approve or deny a swap, not to prioritize which days to fill first in a schedule generation process.
“…Combining deSilva's ‘swap logic’ with Thompson's ‘routing logic’ would not result in the claimed invention. Adding swap constraints to Thompson would merely restrict which routes can be traded; it would not introduce the concept of ranking days by workload to drive the initial schedule creation.”
Examiner respectfully finds Applicant’s argument unpersuasive. See previous argument and Examiner response for this amended limitation further supported by Thompson at ¶ [0057], [0062], [0095], removing the reliance upon DeSilva. Additional details and citations are included in the 103 rejection section below.
B2. Applicant argues on page 12 of remarks 1/6/2026:
“Balusani teaches ranking employees, not ranking days. The claimed invention explicitly requires ‘calculating ... a day rank for each day ... based on a workload measure.’ Balusani's logic is the inverse: it manages demand for time off, whereas the claimed invention manages demand for labor (workload).
“Balusani teaches allocating slots to the highest-ranking person. The claimed invention teaches allocating shifts to the highest-ranking day. A Person of Ordinary Skill in the Art (POSIT A) would not be motivated to apply Balusani’s ‘seniority based employee ranking’ to Thompson's ‘routing system’ to arrive at the claimed ‘workload-based day ranking.’ The optimization goals are fundamentally different (fairness in vacation vs. efficiency in labor allocation).”
Examiner respectfully finds Applicant’s argument unpersuasive.
Examiner points to previous argument and response regarding day ranks. Examiner applies broadest reasonable interpretation of “day” rank as interchangeable with “job” rank, as is common in assigning shifts in a workforce. Although Balusani ranks the workers, Thompson ranks the jobs [EN: days or shifts], removing reliance on Balusani to teach the claim limitation as amended. Examiner submits, in arguendo, even if the optimization goals are different (which may be true for any two systems or methods in the industry), the functions, which are optimizing scheduling of a workforce, are analogous.
Accordingly, the previous pending rejection under 35 USC 103 will be maintained. The 103 rejection is updated in view of the amendments.
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Claim Rejections - 35 USC § 112(b)
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1, 12 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claims 1, 12 recite:
“[..] wherein assembling the schedule comprises matching a first open shift from the ordered list of open shifts to a first day from the ordered list of days;
“assembling, by the processor, (claim 1) / assemble (claim 12) a first schedule for the user according to the ordered list of open shifts” [bolded emphasis added].
Claims 1, 12 are rendered vague and indefinite because it is unclear whether the assembly function in “assembling, by the processor, (claim 1) / assemble (claim 12) a first schedule” is the same as the antecedently recited “wherein assembling the schedule comprises”.
Claims 1, 12 are recommended to recite, as an example only:
“[..]
“assembling, by the processor, (claim 1) / assemble (claim 12) a first schedule for the user according to the ordered list of open shifts, wherein assembling the schedule comprises matching a first open shift from the ordered list of open shifts to a first day from the ordered list of days”.
Appropriate corrections are required.
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Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-21 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claims 1-11, 21 are directed to a method or process which is a statutory category.
Claims 12-20 are directed to a system or machine which is a statutory category.
Step 2A Prong One: The claims recite, describe, or set forth a judicial exception of an abstract idea (see MPEP 2106.04(a)). Specifically, independent claim 1 recites, describe or set forth agreements in the form of contracts, business relations, or managing personal behavior or relationships or interactions between people, including: “querying… for a plurality of shift features, wherein the schedule… includes previous schedule data”, “receiving… schedule preferences”, “validating… the set of open shifts against applicable scheduling rules”, “calculating… a day rank for each day of the set of days based on a workload measure”, “sorting… the set of days based on the day rank to generate an ordered list of days”, “assembling… a first set of user shift features”, “selecting… a score function”, “sorting… the set of validated open shifts based on the open shift score to generate an ordered list of open shifts and the ordered list of days”, “matching a first open shift from the ordered list of open shifts to a first day from the ordered list of days” “assembling… a first schedule”, and “generating a depiction of the first schedule”. Independent claim 12 recites similar language. Collecting shift history data, collecting worker preferences, generating schedule options based on scoring functions for workers, and creating worker schedules fall within agreements in the form of contracts and business relations as they pertain to commercial or legal interactions, or managing personal behavior or relationships or interactions between people, each within the larger abstract grouping of Certain Methods of Organizing Human Activity (MPEP 2106.04(a)(2) II). Accordingly, the claims recite an abstract idea.
Step 2A Prong Two: Independent claims 1, 12 recite the following additional elements: “computer”, “system”, “server computer”, “processor”, “memory”, “database”, and “user interface”. The functions of these additional elements include examples such as “query a schedule database”, “receive schedule preferences”, “assemble a first set of user shift features”, “select a score function”, “compute… an open shift score”, “sort the set of open shifts”, “assemble a first schedule”, and “generate… a depiction of the first schedule.” The additional elements are recited at a high level of generality (i.e. as a generic computer performing functions of searching for, ranking, assembling, and presenting data, etc.) such that they amount to no more than mere instructions to apply the exception using generic computer components. Therefore, these functions can be viewed as not meaningfully different than a business method or mathematical algorithm being applied on a general-purpose computer as tested per MPEP 2106.05(f)(2)(i). The claims are directed to an abstract idea and the judicial exception does not integrate the abstract idea into a practical application.
Step 2B: According to MPEP 2106.05(f)(1), considering whether the claim recites only the idea of a solution or outcome i.e., the claims fail to recite the technological details of how the actual technological solution to the actual technological problem is accomplished. The recitation of claim limitations that attempt to cover an entrepreneurial and thus abstract solution to an entrepreneurial problem with no technological details on how the technological result is accomplished and no description of the mechanism for accomplishing the result do not provide significantly more than the judicial exception.
The dependent claims do not appear to provide any additional computer-based elements, let alone for such additional computer-based elements to integrate the abstract idea into practical application (Step 2A prong two) or providing significantly more (Step 2B).
Further, dependent claims 2-11, 13-21 merely incorporate the additional elements recited in claims 1, 12 along with further narrowing of the abstract idea of claims 1, 12 along with their execution of the abstract idea. New dependent Claim 21 recites “selecting… the score function… is further based on a historical success of the score function resulting in schedule selection”. Specifically, the dependent claims narrow the “computer”, “system”, “server computer”, “processor”, “memory”, “database”, and “user interface” to capabilities such as transmitting, generating, selecting, ordering, calculating, receiving, committing, assembling, sorting, detecting, and comprising various forms of data such as alerts, lists, days, shifts, schedules, scores, features, depictions, conflicts, etc. which, when evaluated per MPEP 2106.05(f)(2) represent mere invocation of computers to perform existing processes. Therefore, the additional elements recited in the claimed invention individually and in combination fail to integrate a judicial exception into a practical application (Step 2A prong two) and for the same reasons they also fail to provide significantly more (Step 2B). Thus, claims 1-21 are reasoned to be patent ineligible.
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REJECTIONS BASED ON PRIOR ART
Examiner Note: Some rejections will contain bracketed comments preceded by an “EN” that will denote an examiner note. This will be placed to further explain a rejection.
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Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102 of this title, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-2, 7, 9-13, 18, 20 are rejected under 35 U.S.C. 103 as being unpatentable over:
DeSilva et al. US 20050004828 A1, hereinafter DeSilva in view of
Balusani et al. US 20200327478 A1, hereinafter Balusani, and in further view of
Thompson US 20170004420 A1, hereinafter Thompson. As per,
Regarding Claim 1: DeSilva teaches:
“A computer-implemented method for schedule generation, the method comprising: (claim 1) / A system, comprising at least one server computer comprising at least one processor and at least one memory, the at least one server computer configured to: (claim 12)
“querying (claim 1) / query (claim 12), by a processor (claim 1), a schedule database for a plurality of shift features, wherein the schedule database includes previous schedule data for a user” (DeSilva ¶ [0033]: Scheduling constraints received in step 105 may include, for example, staff preferences, staff hired profiles, demand profiles, scheduling guidelines, and history… History refers to shifts worked by, or scheduled for, resources [EN: users] over one or more time periods preceding the planning horizon. ¶ [0034]: Data relating to staff preferences, staff hired profiles, demand profiles, scheduling guidelines and history may be further classified as either hard constraints or soft constraints, according to management choice);
“receiving (claim 1) / receive (claim 12), by the processor (claim 1), schedule preferences for the user” (DeSilva ¶ [0033]: Scheduling constraints received in step 105 may include, for example, staff preferences, staff hired profiles, demand profiles, scheduling guidelines, and history. Staff preferences may include, by way of example and not limitation, data such as the time of day and/or the day of week that a worker prefers to work or not to work [Also see Fig. 1 and related text]);
[..]
“computing (claim 1) / compute (claim 12), by the processor (claim 1), for each open shift in the set of [[validated]] open shifts, an open shift score with the score function” (DeSilva ¶ [0046]: In step 230, penalty scores are determined for each available shift according to violations in shift patterns and/or other soft constraints, as will be described in more detail with reference to FIG. 4. [Also see Fig. 2 and related text]);
Although DeSilva discloses scoring open shifts generally for a worker based on his or her preferences and historical data to manage conflicts with soft and hard constraints, DeSilva does not specifically teach narrowing valid open shifts as a subset of open shifts, or the selection of scoring criteria based on shift features and subsequent rank ordering of options used to generate a schedule.
However, Balusani in analogous art of smart work shift scheduling teaches or suggests:
“validating (claim 1) / validate (claim 12), by the processor (claim 1), the set of open shifts against applicable scheduling rules to generate a set of validated open shifts” (See Balusani narrowing valid open shifts as a subset of open shifts at Fig. 14 Step 712: Assign selected week to employee a as new week 1, decrease available allotment for new week; Fig. 15 Step 808: Scan preference #1 of employee #10083 requesting change of week #11 to week #8; Step 810: Assign week #8 to employee #10083 as new week 1, decrease available allotment for week #8);
“assembling (claim 1) / assemble (claim 12), by the processor (claim 1), a first set of user shift features from the plurality of shift features and the schedule preferences” (See Balusani ¶ [0029]: A start time graphical user interface (GUI) control 20a and an end time GUI control 20a are displayed on the user interface 18. In this implementation, each GUI control 20a and 20b is displayed as a slider control by the shift scheduling program 204. The start time GUI control 20a is manipulated by the employee to set a preferred start time [EN: feature], while the end time GUI control 20b is manipulated by the employee to set a preferred end time [EN: feature] of the work shift. In this example, the employee has indicated a time of 7:30 am as the preferred start time, and a time of 3:30 pm as the preferred end time. A location GUI control 22 is displayed for the employee to specify work locations [EN: feature] where the employee would prefer to work, or specify work locations where the employee would not prefer to work. An off day GUI control 24 is displayed for the employee to specify which days of the week [EN: feature] the employee prefers as days off work. [Also see Fig. 4 and related text]);
[..]
“receiving (claim 1) / receive (claim 12), by the processor (claim 1), a set of open shifts for a set of days for the user” (See Balusani Fig. 4 element 24 where user can customize open shift list based on preferred days of the week. End-¶ [0029]: An off day GUI control 24 is displayed for the employee to specify which days of the week the employee prefers as days off work);
“sorting (claim 1) / sort (claim 12), by the processor (claim 1), the set of [[validated]] open shifts based on the open shift scores to generate an ordered list of open shifts and the ordered list of days, wherein assembling the schedule comprises matching a first open shift from the ordered list of open shifts to a first day from the ordered list of days” (See Balusani Fig. 11 Step 512: Sort time slots based on the preferred criteria; Step 514: Sort time slots based on predetermined rules 514; and Step 532: Auto-assign time slot to user during next preference time window in next bid 532 ¶ [0050]: At 512, the server sorts the time slots included in the bidding session based on the preferred criteria inputted by the user. These preferred criteria may be evaluated during the gaps between the bid time windows. [Also see Figs. 4, 5 and related text]);
“assembling (claim 1) / assemble (claim 12), by the processor (claim 1), a first schedule for the user according to the ordered list of open shifts” (See Balusani Fig. 5 element 54, preferred schedule from ordered list, and related text); “and
“generating (claim 1) / generate (claim 12), by the processor (claim 1), for presentation at a user interface, a depiction of the first schedule” (See Balusani Fig. 11 step 538: receive and display time slot assignment).
Balusani and DeSilva are found as analogous art of smart work shift scheduling. It would have been obvious to one skilled in the art, before the effective filing date of the invention, to have modified DeSilva’s preference scheduling of staffing resources system and method to have included Balusani’s teachings around narrowing valid open shifts as a subset of open shifts and the selection of scoring criteria based on shift features and subsequent rank ordering of options used to generate a schedule. The benefit of these additional features would have further improved employees ability to balance their preferred vacation days, work schedules, and work locations (Balusani ¶ [0001-0002]). The predictability of such modifications and/or variations, would have been corroborated by the broad level of skill of one of ordinary skills in the art as articulated by DeSilva in view of Balusani (see MPEP 2143 G).
Further, the claimed invention could have also been viewed as a mere combination of old elements in a similar field of smart work shift scheduling. In such combination each element would have merely performed same organizational and managerial function as it did separately. Thus, one of ordinary skill in the art would have recognized that, given existing technical ability to combine the elements, as evidenced by DeSilva in view of Balusani above, the to- be combined elements would have fit together like pieces of a puzzle in a logical, complementary, technologically feasible and/or economically desirable manner. Thus, it would have been reasoned that the results of the combination would have been predictable (see MPEP 2143 A).
Furthermore, although DeSilva in view of Balusani discloses selecting a score function, it falls short of specifically selecting a score function from a plurality of score functions based on the first set of user shift features, as well as ranking and sorting shifts based on workload.
However,HOH Thompson in analogous art of smart work shift scheduling teaches or suggests:
“calculating (claim 1) / calculate (claim 12), by the processor (claim 1), a day rank for each day of the set of days based on a workload measure” (Thompson ¶ [0057]: Options are ranked by computing a discrete value for each option and then sorting by that value. The score for each job represents the attractiveness of that job to a specific worker and at a specific point in the route creation process. The value of a job varies due to a variety of dynamic conditions, such as traffic, current workload…. ¶ [0095]: The method may also include the step of ranking the scores for each of the set of jobs being considered for assignment to the specific worker at the particular time of day);
“sorting (claim 1) / sort (claim 12), by the processor (claim 1), the set of days based on the day rank to generate an ordered list of days” (Thompson ¶ [0057]: Options are ranked by computing a discrete value for each option and then sorting by that value. The score for each job represents the attractiveness of that job to a specific worker and at a specific point in the route creation process. The value of a job varies due to a variety of dynamic conditions, such as traffic, current workload…. ¶ [0095]: The method may also include the step of ranking the scores for each of the set of jobs being considered for assignment to the specific worker at the particular time of day);
“selecting (claim 1) / select (claim 12), by the processor (claim 1), a score function from a plurality of score functions based on the first set of user shift features” (Thompson ¶ [0059]: Values from several scoring components are combined into a final composite score for each arc available to a worker. Each component returns a value in the range. The individual component weights are scaled using their strengthening coefficients [EN: score function] and added together to produce the final score. ¶ [0062]: … During step 64, for each active worker, each arc, or each job in a set of job locations available to be scheduled, is scored and a ranking of jobs from highest to lowest is generated per worker. ¶ [0094]: The method may include the step of generating a score for each of the set of jobs being considered for assignment to the specific worker at the particular time of day. Each of the scores may be computed from a plurality of factors, and the coefficient representing the appeal for venturing or homing is used to produce at least one of the plurality of factors. The plurality of factors may include at least one of travel distance to a job location and estimated travel time to a job location [EN: user shift features]. ¶ [0095]: The method may also include the step of ranking the scores for each of the set of jobs being considered for assignment to the specific worker at the particular time of day).
Thompson, Balusani and DeSilva are found as analogous art of smart work shift scheduling. It would have been obvious to one skilled in the art, before the effective filing date of the invention, to have modified DeSilva / Balusani’s preference scheduling of staffing resources system and method to have included Thompson teachings around selecting a score function from a plurality of score functions based on the first set of user shift features and ranking and sorting shifts based on workload. The benefit of these additional features would have matched more ideal workers with the type of jobs they are best adapted to service (Thompson ¶ [0019]). The predictability of such modifications and/or variations, would have been corroborated by the broad level of skill of one of ordinary skills in the art as articulated by DeSilva in view of Balusani and Thompson (see MPEP 2143 G).
Further, the claimed invention could have also been viewed as a mere combination of old elements in a similar field of smart work shift scheduling. In such combination each element would have merely performed same organizational and managerial function as it did separately. Thus, one of ordinary skill in the art would have recognized that, given existing technical ability to combine the elements, as evidenced by DeSilva in view of Balusani and Thompson above, the to- be combined elements would have fit together like pieces of a puzzle in a logical, complementary, technologically feasible and/or economically desirable manner. Thus, it would have been reasoned that the results of the combination would have been predictable (see MPEP 2143 A).
Regarding Claims 2, 13: DeSilva / Balusani / Thompson teaches all the limitations of claims 1, 12 above.
DeSilva does not specifically teach alerting the user when the schedule is ready for review.
However, Balusani in analogous art of smart work shift scheduling teaches or suggests: “further comprising transmitting an alert to a user device (claim 2) / wherein the at least one server computer is configured to transmit an alert to a user device (claim 13) , wherein the alert indicates that the first schedule is ready for review” (Balusani end-¶ [0033]: The employee may be notified or reminded of a scheduled bidding session by the shift scheduling program 204).
Rationales to have modified/combined DeSilva / Balusani are above and reincorporated.
Regarding Claims 7, 18: DeSilva / Balusani / Thompson teaches all the limitations of claims 1, 12 above.
DeSilva does not specifically teach the user accepting the schedule and the system committing the first schedule for the user.
However, Balusani in analogous art of smart work shift scheduling teaches or suggests: “receiving (claim 7) / receive (claim 18) a selection indicative of acceptance of the first schedule by the user; and committing (claim 7) / commit (claim 18) the first schedule for the user” (Balusani end-¶ [0051]: …when it is determined that no other user has selected [EN: accepted] the time slot, at 536, the selected time slot is assigned [EN: committed] to the user who selected the time slot during the live bidding time window. At 538, the client device receives from the server an assignment of the given user to the selected time slot…).
Rationales to have modified/combined DeSilva / Balusani / Thompson are above and reincorporated.
Regarding Claims 9, 20: DeSilva / Balusani / Thompson teaches all the limitations of claims 1, 12 above.
DeSilva further teaches:
[..]
“computing (claim 9) / compute (claim 20), for each open shift in the second set of open shifts, a second open shift score with the score function” (DeSilva ¶ [0046]: In step 230, penalty scores are determined for each available shift according to violations in shift patterns and/or other soft constraints, as will be described in more detail with reference to FIG. 4. [Also see Fig. 2 and related text]);
[..]
Although DeSilva discloses calculating shift scores for subsequent open shifts, DeSilva does not specifically teach detecting a scheduling conflict with another user and repeating the process as described in claims 1, 12.
However, Balusani in analogous art of smart work shift scheduling teaches or suggests:
“receiving (claim 9) / receive (claim 20) a selection indicative of acceptance of the first schedule by the user” (Balusani mid-¶ [0051]: At 522, during the live bidding time window, the client device receives a given user input of a time slot selection [EN: acceptance] among the time slots included in the list during a live bidding time window, and sends the time slot selection to the server during the live bidding time window);
“detecting (claim 9) / detect (claim 20) a scheduling conflict in the first schedule with a schedule of a second user” (Balusani end-¶ [0051]: At 530, the server determines whether the selected time slot has already been selected by another user); “and
“receiving (claim 9) / receive (claim 20) a second set of open shifts for a set of days for the user” (See Balusani Fig. 4 element 24 where user can customize open shift list based on preferred days of the week. End-¶ [0029]: An off day GUI control 24 is displayed for the employee to specify which days of the week the employee prefers as days off work);
[..]
“sorting (claim 9) / sort (claim 20) the second set of open shifts based on the second open shift scores to generate a second ordered list of open shifts” (See Balusani Fig. 11 step 512: sort time slots based on the preferred criteria. ¶ [0050]: At 512, the server sorts the time slots included in the bidding session based on the preferred criteria inputted by the user. These preferred criteria may be evaluated during the gaps between the bid time windows. [Also see Figs. 4, 5 and related text]);
“assembling (claim 9) / assemble (claim 20) a second schedule for the user according to the second ordered list of open shifts” (Balusani end-¶ [0051]: When it is determined by the server that the time slot has already been selected by another user, at 534, the server assigns the time slots based on predetermined sort rules and preferred criteria); “and
“generating (claim 9) / generate (claim 20), for presentation at the user interface, a depiction of the second schedule” (See Balusani Fig. 11 step 538: receive and display time slot assignment).
Rationales to have modified/combined DeSilva / Balusani / Thompson are above and reincorporated.
Regarding Claim 10: DeSilva / Balusani / Thompson teaches all the limitations of claim 1 above.
DeSilva further teaches “wherein the plurality of shift features comprises at least one of user work location history, user co-worker affinity, user workday frequency, open shift skill and certification requirements, or user time of day work frequency” (DeSilva ¶ [0046]: Scheduling constraints received in step 105 may include, for example, staff preferences, staff hired profiles, demand profiles, scheduling guidelines, and history. Staff preferences may include, by way of example and not limitation, data such as the time of day and/or the day of week that a worker prefers to work or not to work. Staff hired profiles may include, for instance, a service date or other indication of seniority, a designation of employee status as a full or part-time worker, and/or a skills classification).
Regarding Claim 11: DeSilva / Balusani / Thompson teaches all the limitations of claim 1 above.
DeSilva further teaches “wherein the score function comprises a weighted sum function” (DeSilva ¶ [0099]: The process continues to step 910 by establishing scheduling strategies. In one embodiment of the invention, these scheduling strategies are read from step 115. In another embodiment, scheduling strategies are adjusted by the user in order to run scenarios on the effect of strategy changes, such as a change to the weighting of employee preferences).
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Claims 3-6, 8, 14-17, 19, 21 are rejected under 35 U.S.C. 103 as being unpatentable over:
DeSilva / Balusani / Thompson as applied above, in further view of
Bowles US 20240193509 A1, hereinafter Bowles. As per,
Regarding Claims 3, 14: DeSilva / Balusani / Thompson teaches all of the limitations of claims 1, 12 above.
Although DeSilva / Balusani teaches generating an ordered list of time slots for workers, DeSilva / Balusani does not specifically teach associating the ordered list of shifts with an ordered list of days.
However, Bowles in analogous art of smart work shift scheduling teaches or suggests: “wherein assembling the first schedule for the user comprises:
“generating an ordered list of days from the set of days; selecting a first day from the ordered list of days; and selecting from the ordered list of open shifts a first open shift that corresponds to the first day” (Bowles mid-¶ [0095]: The workers each receive an individual schedule request such as the request 532 [EN: ordered list of days] shown in FIG. 14. The request 532 includes the number of shifts available for each day of the week. The workers select shifts using the selection interface 534 shown in FIG. 15. The user makes selections 536 of shifts based on the shifts available for pickup. The system approves or disapproves the selections).
Bowles, Thompson, Balusani and DeSilva are found as analogous art of smart work shift scheduling. It would have been obvious to one skilled in the art, before the effective filing date of the invention, to have modified DeSilva / Balusani / Thompson’s preference scheduling of staffing resources system and method to have included Bowles’ teachings around the associating the ordered list of shifts with an ordered list of days. The benefit of these additional features would have further improved scheduling efficiency based on business requirements and worker inputs (Bowles ¶ [0005]). The predictability of such modifications and/or variations, would have been corroborated by the broad level of skill of one of ordinary skills in the art as articulated by DeSilva / Balusani / Thompson and in further view of Bowles (see MPEP 2143 G).
Further, the claimed invention could have also been viewed as a mere combination of old elements in a similar field of smart work shift scheduling. In such combination each element would have merely performed same organizational and managerial function as it did separately. Thus, one of ordinary skill in the art would have recognized that, given existing technical ability to combine the elements, as evidenced by DeSilva / Balusani / Thompson and in further view of Bowles above, the to- be combined elements would have fit together like pieces of a puzzle in a logical, complementary, technologically feasible and/or economically desirable manner. Thus, it would have been reasoned that the results of the combination would have been predictable (see MPEP 2143 A).
Regarding Claims 4, 15: DeSilva / Balusani / Thompson / Bowles teaches all of the limitations of claims 3, 14 above.
Although DeSilva / Balusani / Thompson in combination teaches generating an ordered list of time slots for workers, it does not specifically teach associating the ordered list of shifts with an ordered list of days.
However, Bowles in analogous art of smart work shift scheduling teaches or suggests: “wherein assembling the first schedule for the user comprises:
“selecting a second day from the ordered list of days; and selecting from the ordered list of open shifts a first open shift that corresponds to the second day” (See in Bowles Fig. 15 multiple instances of element 536 day/shift selection. Mid-¶ [0095]: The workers each receive an individual schedule request such as the request 532 [EN: ordered list of days] shown in FIG. 14. The request 532 includes the number of shifts available for each day of the week. The workers select shifts using the selection interface 534 shown in FIG. 15. The user makes selections 536 of shifts based on the shifts available for pickup. The system approves or disapproves the selections).
Rationales to have modified/combined DeSilva / Balusani / Thompson / Bowles are above and reincorporated.
Regardings Claim 5, 16: DeSilva / Balusani / Thompson / Bowles teaches all of the limitations of claims 4, 15 above.
Although DeSilva / Balusani / Thompson in combination teaches generating an ordered list of time slots for workers, it does not specifically teach associating the ordered list of shifts with an ordered list of days or a number of open shifts available for each day.
However, Bowles in analogous art of smart work shift scheduling teaches or suggests: “wherein generating the ordered list of days comprises:
ordering the set of days according to a number of open shifts available for each day” (Bowles mid-¶ [0079]: The system 500 receives the amount of pick-up shifts, identifies the quantity of shifts needed each day, and outputs employee requests based on availability needed. [Also see Fig. 9A, Fig. 13 and related text]).
Rationales to have modified/combined DeSilva / Balusani / Thompson / Bowles are above and reincorporated.
Regarding Claims 6, 17: DeSilva / Balusani / Thompson / Bowles teaches all of the limitations of claims 4, 15 above.
DeSilva further teaches “wherein generating the ordered list of days comprises:
“calculating a (DeSilva ¶ [0046]: In step 230, penalty scores are determined for each available shift according to violations in shift patterns and/or other soft constraints, as will be described in more detail with reference to FIG. 4. ¶ [0078]: Next, the process reads the constraints and strategies for daily scheduling in step 610. The constraints may include staff qualifications. [Also see Fig. 2 and related text]).
Although DeSilva discloses applying worker qualifications for generating scores, DeSilva does not explicitly teach the application of scores to specific days, as indicated with by strikethrough above.
DeSilva also does not specifically teach ordering the set of days according to the day score.
However, Bowles in analogous art of smart work shift scheduling teaches or suggests: “calculating a day score for each day in the set (See Bowles Fig. 16, 17, 18 bonus/incentive levels [EN: score] per day based on worker credential. Mid [0092]: The selected incentive is then applied for qualified workers in the scheduling system. The user can select bonus credentials that need to be met and/or criteria that can disqualify an individual. The user can remove disqualifying parameters for incentives on an individual basis per day or shift.
Furthermore, Balusani in analogous art of smart work shift scheduling teaches or suggests: “ordering the set of days according to the day score” (See Balusani Fig. 11 step 512: sort time slots based on the preferred criteria. ¶ [0050]: At 512, the server sorts the time slots included in the bidding session based on the preferred criteria inputted by the user. These preferred criteria may be evaluated during the gaps between the bid time windows. [Also see Figs. 4, 5 and related text]).
Rationales to have modified/combined DeSilva / Balusani / Thompson / Bowles are above and reincorporated.
Regarding Claims 8, 19: DeSilva / Balusani / Thompson / Bowles teaches all of the limitations of claims 1, 12 above.
DeSilva further teaches:
[..]
“computing (claim 8) / compute (claim 19), for each open shift in the set of open shifts, a second open shift score with the second score function” (DeSilva ¶ [0046]: In step 230, penalty scores are determined for each available shift according to violations in shift patterns and/or other soft constraints, as will be described in more detail with reference to FIG. 4. [Also see Fig. 2 and related text]).
[..]
Although DeSilva discloses calculating shift scores for subsequent open shifts, DeSilva does not specifically teach receiving a rejection for the schedule and repeating the process as described in claims 1, 12 with a second set of shift scores.
However, Bowles in analogous art of smart work shift scheduling teaches or suggests: “receiving (claim 8) / receive (claim 19) a selection indicative of rejection of the first schedule (See Bowles Fig. 7 steps 310, 314, 316 for rejecting shifts. ¶ [0055]: The shift selection system 18 receives 310, from the shift worker device 110, at least one shift selection 204 based on the plurality of unassigned work shifts 202. The shift selection system 18 approves 312 the shift selection 204 if the shift selection meets at least one selection parameter. The shift selection system 18 rejects 314 the shift selection 204 if the shift selection does not meet the at least one selection parameter).
[..]
Despite Bowles falling short of disclosing the schedule rejection specifically being performed by the worker as indicated by strikethrough above, Balusani in analogous art of smart work shift scheduling teaches or suggests worker discretion for accepting schedules (See Balusani Fig. 5 element 58 where worker chooses whether to pick [or alternatively, by default, reject] a proposed shift).
Furthermore, Balusani teaches or suggests:
[..]
“assembling (claim 8) / assemble (claim 19) a second set of user shift features from the plurality of shift features and the schedule preferences” (See Balusani ¶ [0029]: A start time graphical user interface (GUI) control 20a and an end time GUI control 20a are displayed on the user interface 18. In this implementation, each GUI control 20a and 20b is displayed as a slider control by the shift scheduling program 204. The start time GUI control 20a is manipulated by the employee to set a preferred start time [EN: feature], while the end time GUI control 20b is manipulated by the employee to set a preferred end time [EN: feature] of the work shift. In this example, the employee has indicated a time of 7:30 am as the preferred start time, and a time of 3:30 pm as the preferred end time. A location GUI control 22 is displayed for the employee to specify work locations [EN: feature] where the employee would prefer to work, or specify work locations where the employee would not prefer to work. An off day GUI control 24 is displayed for the employee to specify which days of the week [EN: feature] the employee prefers as days off work. [Also see Fig. 4 and related text]);
[..]
“sorting (claim 8) / sort (claim 19) the set of open shifts based on the second open shift scores to generate a second ordered list of open shifts” (See Balusani Fig. 11 step 512: sort time slots based on the preferred criteria. ¶ [0050]: At 512, the server sorts the time slots included in the bidding session based on the preferred criteria inputted by the user. These preferred criteria may be evaluated during the gaps between the bid time windows. [Also see Figs. 4, 5 and related text]);
“assembling (claim 8) / assemble (claim 19) a second schedule for the user according to the second ordered list of open shifts” (See Balusani Fig. 5 element 54, preferred schedule from ordered list, and related text); “and
“generating (claim 8) / generate (claim 19), for presentation at the user interface, a depiction of the second schedule” (See Balusani Fig. 11 step 538: receive and display time slot assignment).
Further still, although DeSilva / Balusani / Bowles in combination discloses selecting a score function, it falls short of specifically selecting a second score function for the second set of user shift features. However,HOH Thompson in analogous art of smart work shift scheduling teaches or suggests:
“selecting (claim 8) / select (claim 19) a second score function for the second set of user shift features” (Thompson ¶ [0059]: Values from several scoring components are combined into a final composite score for each arc available to a worker. Each component returns a value in the range. The individual component weights are scaled using their strengthening coefficients [EN: score function] and added together to produce the final score. ¶ [0062]: … During step 64, for each active worker, each arc, or each job in a set of job locations available to be scheduled, is scored and a ranking of jobs from highest to lowest is generated per worker. ¶ [0094]: The method may include the step of generating a score for each of the set of jobs being considered for assignment to the specific worker at the particular time of day. Each of the scores may be computed from a plurality of factors, and the coefficient representing the appeal for venturing or homing is used to produce at least one of the plurality of factors. The plurality of factors may include at least one of travel distance to a job location and estimated travel time to a job location [EN: user shift features]. ¶ [0095]: The method may also include the step of ranking the scores for each of the set of jobs being considered for assignment to the specific worker at the particular time of day).
Rationales to have modified/combined DeSilva / Balusani / Thompson / Bowles are above and reincorporated.
Regarding Claim 21: DeSilva / Balusani / Thompson / Bowles teaches all the limitations of claim 1 above.
Although DeSilva / Balusani / Thompson in combination teaches selecting a score function to increase likelihood of scheduling success, it does not teach the incorporation of historical shift selection success into the calculation.
However, Bowles in analogous art of smart work shift scheduling teaches or suggests:
“wherein selecting, by the processor, the score function from the plurality of score functions is further based on a historical success of the score function resulting in schedule selection” (Bowles end-¶ [0057]: In addition, the shift selection system 18 may store the initial and alternative shift selections of the shift workers in the memory. Accordingly, the shift selection system 18 is able to identify and generate reports for popular or unpopular shifts, patterns in the shift workers selections, and other statistics for use in future scheduling. In some embodiments, the shift selection system 18 may predict at least some shift selections for the shift workers based on historical data. As a result, the shift selection system 18 facilitates quicker and easier shift selections by the shift workers and resource planning and leveling by the business).
Bowles, Thompson, Balusani and DeSilva are found as analogous art of smart work shift scheduling. It would have been obvious to one skilled in the art, before the effective filing date of the invention, to have modified DeSilva / Balusani / Thompson’s preference scheduling of staffing resources system and method to have included Bowles’ teachings around applying historical shift selection success to scoring and predicting future shifts. The benefit of these additional features would have further improved scheduling efficiency based on business requirements and worker inputs (Bowles ¶ [0005]). The predictability of such modifications and/or variations, would have been corroborated by the broad level of skill of one of ordinary skills in the art as articulated by DeSilva / Balusani / Thompson and in further view of Bowles (see MPEP 2143 G).
Further, the claimed invention could have also been viewed as a mere combination of old elements in a similar field of smart work shift scheduling. In such combination each element would have merely performed same organizational and managerial function as it did separately. Thus, one of ordinary skill in the art would have recognized that, given existing technical ability to combine the elements, as evidenced by DeSilva / Balusani / Thompson and in further view of Bowles above, the to- be combined elements would have fit together like pieces of a puzzle in a logical, complementary, technologically feasible and/or economically desirable manner. Thus, it would have been reasoned that the results of the combination would have been predictable (see MPEP 2143 A).
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Conclusion
The following art is made of record and considered pertinent to Applicant’s disclosure:
Aslam et al. US 20220198353 A1, System and method for schedule management.
Ásgeirsson, Eyjólfur Ingi, and Guðríður Lilla Sigurðardóttir. "Near-optimal MIP solutions for preference based self-scheduling." Annals of Operations Research 239 (2016): 273-293. https://link.springer.com/content/pdf/10.1007/s10479-014-1597-3.pdf
Absher et al. US 20180025309 A1, Shift worker platform.
Barni, Meghan M. US 20050177409 A1, Method and computer system for schedule bidding.
Beshears US 20070050228 A1, Schedule management.
Birru; Dagnachew et al. US 20230360783 A1, Method and system for optimal scheduling of nursing services.
Brown; Samuel et al. US 20200411170 A1, Machine-learning framework for coordinating and optimizing healthcare resource utilization and delivery of healthcare services across an integrated healthcare system.
Cartier et al. CA 2593371 A1, System and method for on-call scheduling.
Garcia et al. US 20060224477 A1, Automated auction method for staffing work shifts.
Guiffre et al. US 20220180266 A1, Attribute-based shift allocation.
Hedlund, Henrik E. et al. US 20040267591 A1, System and method for dynamic scheduling of personnel.
Kinney US 8401884 B1, Electronic scheduling for work Shifts.
LaJoie; Tom et al. US 20080319822 A1, Method and system for creating and trading schedules.
Limaj; Idriz et al. US 20190108469 A1, Schedule management systems and methods.
Martin; Nicholas Duane et al. US 20200349494 A1, Automated scheduling assistant for a workforce management system.
Narasimhan et al. US 20050096962 A1, Methods and systems for assigning workshifts.
Singh; Amritpal et al. US 20220067632 A1, Scheduling optimization.
Taheri; Soha Peter et al. US 20210407658 A1, Data processing systems for scheduling work shifts, such as physician work shifts.
Vajracharya, Suvas et al. US 20050125278 A1, Method and apparatus for queue-based automated staff scheduling.
Wayne et al. US 20240020756 A1, Apparatus and methods for enabling workers to compete for currently upcoming shifts.
Westland et al. US 10572844 B1, Determining employee shift schedules.
Yang; Jin US 20230229993 A1, Shift design and assignment system with efficient incremental solution.
Martin; Kathleen Pursell et al. US 20230162843 A1, Systems and methods for workload management.
Boehmer; Tiffany D. et al. US 7325190 B1, Interface system and method of building rules and constraints for a resource scheduling system.
Andre; David et al. US 6278978 B1, Agent scheduling system and method having improved post-processing step.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to REED M. BOND whose telephone number is (571) 270-0585. The examiner can normally be reached Monday - Friday 8:00 am - 5:00 pm.
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/REED M. BOND/Examiner, Art Unit 3624 March 24, 2026
/HAMZEH OBAID/Primary Examiner, Art Unit 3624 March 27, 2026