DETAILED ACTION
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 .
Notice to Applicant
The following is a Final Office action. In response to Examiner’s Non-Final Rejection of 05/18/2026, Applicant, on 08/11/2026, amended claims. Claims 1-24 are pending in this application and have been rejected below.
Response to Arguments
Applicant's arguments filed 08/11/2026 have been fully considered, but they are not fully persuasive. The updated 35 USC § 103 and 101 rejections of claims 1-24 are applied in light of Applicant's amendments.
The Applicant argues “the Applicant amends claim 1 to further reflect a technical improvement described in the specification at paragraphs [0010] and [0011].” (Remarks 08/11/2026).
In response, the Examiner respectfully disagrees. The claimed subject matter, is directed to an abstract idea by reciting mathematical relationships, mathematical formulas or equations, mathematical calculations which falls into the “Mathematical concepts” group; and by reciting fundamental economic principles or practices (including hedging, insurance, mitigating risk); commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions) which falls into the “Certain methods of organizing human activity” within the enumerated groupings of abstract ideas.
A claim that recites a mathematical calculation, when the claim is given its broadest reasonable interpretation in light of the specification, will be considered as falling within the "mathematical concepts" grouping. A mathematical calculation is a mathematical operation (such as multiplication) or an act of calculating using mathematical methods to determine a variable or number, e.g., performing an arithmetic operation such as exponentiation. There is no particular word or set of words that indicates a claim recites a mathematical calculation. That is, a claim does not have to recite the word "calculating" in order to be considered a mathematical calculation. For example, a step of "determining" a variable or number using mathematical methods or "performing" a mathematical operation may also be considered mathematical calculations when the broadest reasonable interpretation of the claim in light of the specification encompasses a mathematical calculation.
The claimed subject matter is merely claims a method for calculating and analyzing information regarding zone data. Although it may be intended to be performed in a digital environment, the claimed subject matter (as currently claimed in the independent claim) speaks to the calculating and analyzing data. Such steps are not tied to the technological realm, but rather utilizing technology to perform the abstract ideas (mathematical concepts). The steps of calculating data, training/updating models, and generating a model/trend line can be performed by a human (mental process/pen and paper). The practice of calculating information and constructing models with set parameters and timelines can be performed without computers and thus are not tied to technology nor improving technology.
The computational efficiency stated in paragraph 0010-0011 of the Applicant spec arsies from “the subsequent assignment of particular suppliers to particular demand nodes,” which claim 1 does not recite, so the claim does not reflect the asserted improvement (MPEP 2106.014(d)(1)). The benefit described in 0011, “lower total travel time or distance across all suppliers,” is a logistical omptimization improvement to the abstract idea, and not the functioning of a computer or another technology (MPEP 2106.05(a))
The solution mentioned in the amended limitation is not implemented/integrated into technology and thus not an improvement to the technical field. Further, there is no integration into a practical application as the claims can be interpreted as humans per se, as the claims fail to tie the steps to technology; insignificant extra solution activities (which are merely calculating and/or analyzing data).
The steps relied upon by the Applicant as recited does not improve upon another technology, the functioning of the computer itself, or allow the computer to perform a function not previously performable by a computer. The claims do not mention to any use of a specialized computer and/or processor. The Applicant is using generic computing components (processors) to perform in a generic/expected way (obtaining and analyzing data).The abstract idea is not particular to a technological environment, but is merely being applied to a computer realm. The process of calculating and analyzing data specifically for zone information , and performing additional analysis can be done without a computer, and thus the claims are not “necessarily rooted", but rather they are utilizing computer technology to perform the abstract idea. The Examiner does not recognize any elements of the Applicant's claims and/or specification that would improve or allow the computer to perform a function(s) not previously performable by the computer, or improve the functioning of the computer itself. It is insufficient to indicate that the claims are novel and non-obvious, and thus contain “something more.” Just because the components may perform a specialized function does not mean that that the computer components are specialized. As such the application of the abstract idea of collecting and analyzing data regarding purchase information, and performing correlation analysis is insufficient to demonstrate an improvement to the technology.
The additional elements have been evaluated, but fail to integrate the abstract idea into a practical application because they amount to using generic computing elements or instructions (software) to perform the abstract idea, similar to adding the words “apply it” (or an equivalent), which merely serves to link the use of the judicial exception to a particular technological environment (generic computing environment). See MPEP 2106.05(f) and 2106.05(h).
The use of Artificial Intelligence (AI), machine learning (ML) models, and/or artificial neural networks (ANN) fall within the realm of abstract ideas. They are, at their core, mathematical algorithms implemented on a computer. As highlighted in Examples 47-49 of the 2024 Patent Subject Matter Eligibility Guidance, the USPTO has consistently viewed claims directed to such models as being drawn to abstract ideas. These examples illustrate claims that, while couched in the language of specific applications, ultimately boil down to mathematical relationships and calculations.
For instance, Applicant claims "wherein the probability value is generated by executing a neural network." While this claim appears to have a practical application, a closer examination reveals that the core of the invention is the underlying mathematical model and its training process. Furthermore, even if the claim recites specific steps related to data collection, preprocessing, or post-processing, these steps often represent well-understood, conventional activities. As demonstrated in Examples 47-49, adding such conventional elements to a claim directed to an abstract idea does not necessarily transform it into a patent-eligible application. These examples illustrate situations where the additional steps were deemed insufficient to provide an "inventive concept" that meaningfully narrowed the scope of the abstract idea. In the context of machine learning, simply collecting and preparing data for input into a model, or applying the model's output to a particular problem, falls into this category of conventional activity. The Applicant has not created a new learning algorithm, but rather optimizing existing algorithm(s) or the application of known techniques to a new dataset. Such incremental advancements, while potentially valuable for business, do not automatically confer patent eligibility or a technological improvement. As highlighted in the Alice framework, the mere recitation of known components or processes does not necessarily amount to an inventive concept.
Applicant’s arguments with respect to the rejection to the claims of 35 U.S.C. 103 have been considered but are moot because the arguments do not apply to the current combination of references being used in the current rejection. In light of Applicants amendments and arguments the Examiner updated the search and provided new art to reject the claim limitations.
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 1-24 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-patentable subject matter. The claims are directed to an abstract idea without significantly more.
Claims 1-24 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The judicial exception is not integrated into a practical application. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception.
With respect to Step 1 of the eligibility inquiry (as explained in MPEP 2106), it is first noted that the method (claims 1-8 and 18), system (claims 9-16), and CRM (claims 17 and 19-24) are directed to potentially eligible categories of subject matter (i.e., process, machine, and article of manufacture respectively). Thus, Step 1 is satisfied.
With respect to Step 2, and in particular Step 2A Prong One, it is next noted that the claims recite an abstract idea by reciting mathematical relationships, mathematical formulas or equations, mathematical calculations which falls into the “Mathematical concepts” group; and by reciting fundamental economic principles or practices (including hedging, insurance, mitigating risk); commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions) which falls into the “Certain methods of organizing human activity” within the enumerated groupings of abstract ideas. The mere nominal recitation of a generic computer does not take the claim limitation out of methods of organizing human activity or the mathematical concepts grouping.
A claim that recites a mathematical calculation, when the claim is given its broadest reasonable interpretation in light of the specification, will be considered as falling within the "mathematical concepts" grouping. A mathematical calculation is a mathematical operation (such as multiplication) or an act of calculating using mathematical methods to determine a variable or number, e.g., performing an arithmetic operation such as exponentiation. There is no particular word or set of words that indicates a claim recites a mathematical calculation. That is, a claim does not have to recite the word "calculating" in order to be considered a mathematical calculation. For example, a step of "determining" a variable or number using mathematical methods or "performing" a mathematical operation may also be considered mathematical calculations when the broadest reasonable interpretation of the claim in light of the specification encompasses a mathematical calculation.
The limitations reciting the abstract idea(s), as set forth in exemplary claim 1, are: generating… a plurality of zone configurations… each zone configuration of the plurality of zone configurations including a respective set of zones among a plurality of sets of zones, wherein generating the plurality of zone configurations comprises: to cluster the plurality of demand nodes into thethat are eligible for the respective set of zones[[,]]; and determining a respective total distance, of a plurality of respective total distances, for the zone configuration based on (i) the distances and (ii) the supply node allocations; selecting…a particular zone configuration, from among the plurality of zone configurations, having a lowest total distance of the plurality of respective total distances; storing…one or more data objects representing the particular zone configuration; Independent claims 9 and 17 recite the CRM and system for performing the method of independent claim 1 without adding significantly more. Thus, the same rationale/analysis is applied.
With respect to Step 2A Prong Two, the judicial exception is not integrated into a practical application. The additional elements are directed to: A computer-implemented method comprising… by one or more processors… at least by applying a machine learning (ML) model… by the one or more processors and in a memory… updating, by the one or more processors, a schedulinq system with the one or more data obiects; A system comprising: a memory; and one or more processors communicatively coupled to the memory, the one or more processors…; One or more non-transitory computer-readable storage media including instructions that, when executed by one or more processors, cause the one or more processors to…; (as recited in claims 1, 9, and 17). However, these elements fail to integrate the abstract idea into a practical application because they fail to provide an improvement to the functioning of a computer or to any other technology or technical field, fail to apply the exception with a particular machine, fail to apply the judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, fail to effect a transformation of a particular article to a different state or thing, and fail to apply/use the abstract idea in a meaningful way beyond generally linking the use of the judicial exception to a particular technological environment.
Accordingly, because the Step 2A Prong One and Prong Two analysis resulted in the conclusion that the claims are directed to an abstract idea, additional analysis under Step 2B of the eligibility inquiry must be conducted in order to determine whether any claim element or combination of elements amount to significantly more than the judicial exception.
With respect to Step 2B of the eligibility inquiry, it has been determined that the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. The additional limitation(s) is/are directed to: A computer-implemented method comprising… by one or more processors… at least by applying a machine learning (ML) model… by the one or more processors and in a memory… updating, by the one or more processors, a schedulinq system with the one or more data obiects; A system comprising: a memory; and one or more processors communicatively coupled to the memory, the one or more processors…; One or more non-transitory computer-readable storage media including instructions that, when executed by one or more processors, cause the one or more processors to…; (as recited in claims 1, 9, and 17) for implementing the claim steps/functions. These elements have been considered, but merely serve to tie the invention to a particular operating environment (i.e., computer-based implementation), though at a very high level of generality and without imposing meaningful limitation on the scope of the claim.
The additional elements have been evaluated, but fail to integrate the abstract idea into a practical application because they amount to using generic computing elements or instructions (software) to perform the abstract idea, similar to adding the words “apply it” (or an equivalent), which merely serves to link the use of the judicial exception to a particular technological environment (generic computing environment). See MPEP 2106.05(f) and 2106.05(h). Even if the acquiring steps are considered as additional elements, these steps at most amount to insignificant extra-solution activity accomplished via receiving/transmitting data, which is not enough to amount to a practical application. See MPEP 2106.05(g).
In addition, Applicant’s Specification (paragraph [0022]) describes generic off-the-shelf computer-based elements for implementing the claimed invention, and which does not amount to significantly more than the abstract idea, which is not enough to transform an abstract idea into eligible subject matter. Such generic, high-level, and nominal involvement of a computer or computer-based elements for carrying out the invention merely serves to tie the abstract idea to a particular technological environment, which is not enough to render the claims patent-eligible, as noted at pg. 74624 of Federal Register/Vol. 79, No. 241, citing Alice, which in turn cites Mayo. See, e.g., Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network).
In addition, when taken as an ordered combination, the ordered combination adds nothing that is not already present as when the elements are taken individually. There is no indication that the combination of elements integrate the abstract idea into a practical application. Their collective functions merely provide conventional computer implementation. Therefore, when viewed as a whole, these additional claim elements do not provide meaningful limitations to transform the abstract idea into a practical application of the abstract idea or that the ordered combination amounts to significantly more than the abstract idea itself. Further, the courts have found the presentation of data to be a well-understood, routine, conventional activity, OIP Techs., 788 F.3d at 1362-63, 115 USPQ2d at 1092-93 (see MPEP 2106.05(d)).
The dependent claims (2-8, 10-16, and 18-24) are directed to the same abstract idea as recited in the independent claims, and merely incorporate additional details that narrow the abstract idea via additional details of the abstract idea. For example claims 2-8 “summing the times or distances from (i) the demand nodes to a zone centroid or a zone medoid for the respective set of zones and (ii) the supply nodes to the zone centroid or the zone medoid for the respective set of zones; wherein the ML model comprises a k-means clustering model; wherein each zone configuration of the plurality of zone configurations consists of a different number of zones; verifying that an allocation of supply nodes to the respective set of zones does not exceed a maximum count for each supply node, wherein the maximum count is a maximum number of demand nodes that can be assigned to a single supply node; verifying that an allocation of supply nodes to the respective set of zones equals or exceeds a minimum count for each supply node, wherein the minimum count is a minimum number of demand nodes that can be assigned to a single supply node; determining, by the one or more processors and for one or more of the supply nodes, a zone assignment based on the particular zone configuration, wherein the zone assignment comprises a single zone of the plurality of respective zones assigned to each of the one or more supply nodes; and causing, by the one or more processors, a display to present a visual indication of the zone assignment; wherein determining the supply node allocations for the respective set of zones included in the zone configuration comprises minimizing a total cost for the zone configuration using an objective function”, without additional elements that integrate the abstract idea into a practical application and without additional elements that amount to significantly more to the claims. The remaining dependent claims (10-16 and 18-24) recite the CRM and system for performing the method of claims 2-8. Thus, the same rationale/analysis is applied. Thus, all dependent claims have been fully considered, however, these claims are similarly directed to the abstract idea itself, without integrating it into a practical application and with, at most, a general-purpose computer that serves to tie the idea to a particular technological environment, which does not add significantly more to the claims.
The ordered combination of elements in the dependent claims (including the limitations inherited from the parent claim(s)) add nothing that is not already present as when the elements are taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide conventional computer implementation. Accordingly, the subject matter encompassed by the dependent claims fails to amount to significantly more than the abstract idea itself.
Claim Rejections - 35 USC § 103
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 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.
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, 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.
Claims 1-24 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. PGPub 20220374452 (hereinafter “Salchert”) et al., in view of U.S. PGPub 20180349412 to (hereinafter “Waldeck”) et al., in further view of U.S. 20100088146 (hereinafter “Zhong”) et al.
As per claim 1, Salchert teaches a computer-implemented method comprising:
generating, by one or more processors, a plurality of zone configurations, each zone configuration of the plurality of zone configurations including a respective set of zones among a plurality of sets of zones, wherein generating the plurality of zone configurations comprises:0072-0079: “assume that the territory alignment task requiring a machine solution is to assign the Zip codes regions of FIG. 11 among either three or four entities or sales reps… Based on the nineteen paths of FIG. 15, alignments or solutions having three territories or four territories may be formed. FIG. 16 illustrates the digital map of FIG. 15 in which three territories are defined.”
determining supply node allocations for the respective set of zones included in the zone configuration based on distances between (i) demand nodes, of the plurality of demand nodes, that are associated with the respective set of zones and (ii) supply nodes, of a plurality of supply nodes, that are eligible for the respective set of zones;
0051: “ Assume that the map of FIG. 1 is to be divided into four (4) territories that are associated with entities or representatives A, B, C, D. Each of A, B, C, D is assigned to a relatively high-valued cell in each of four (4) quadrants of the map. FIG. 2 illustrates the map of FIG. 1 in which the high-valued cells are circled. Four high-value cells 202, 204, 206, 208 are defined. In one embodiment, four (4) initial territory definitions 210, 212, 214, 216 are assigned, each including only cells for which the assigned entity is closer than any other entity, assuming the distance between all adjacent cells is the same….0093: the data table could comprise a column storing a first Zip code, a second Zip code, a distance between centroid points of the two Zip codes, and an estimated travel time for travel between the centroids, with rows of the foregoing form for every pair of Zip codes that represents a unique adjacency.”
determining a respective [[cost]] total distance, of [[the]] a plurality of respective [[costs]] total distances, for the zone configuration based on (i) the 702 among the twenty are identified with reference numerals, as examples. The relative compactness of each territory may be measured by calculating the least cumulative distance or travel from any one section center 702 to the other four, allowing air travel over white space.”
storing, by the one or more processors and in a memory, by the one or more processors, one or more data objects representing the particular zone configuration;0043: “creating and storing, in digital data storage, territory data comprising two or more territory definitions and associating all the existing Constructal groups with one of the two or more territory definitions, the territory definitions defining balanced geographic territories in the geographical map; each of the nearest neighbor units, cluster starting units, branches, channels, and groups being stored in the array memory; programmatically transmitting the territory data to one or more of a set of presentation instructions and an external application computer…0084: execution of the functions results in generating and digitally writing territory map data 1720 in a digital data storage system, which may be the same system as for map data 1702, metric data 1704, or a different system.”
Salchert may not explicitly teach the following. However, Waldeck teaches:
applying a machine learning (ML) model to demand node data indicating locations of a plurality of demand nodes to cluster the plurality of demand nodes into the500, that may be performed in connection with step 104 of process 100 (shown in FIG. 1). Process 500 may begin at step 502. At step 502, the system may group the resources into clusters based on proximity of the resources to each other. The number of clusters may be determined by a user. The clusters may be determined using spatial k-means clustering…0155: At initial data load 2004, a K-means clustering algorithm is run on the latitude-longitude coordinates of attendee locations utilizing Haversine distance calculations.”
selecting, by the one or more processors, a particular zone configuration, from among the plurality of zone configurations, having a lowest total distance of the plurality of respective total distances; 0045: “The systems and methods described herein may determine the optimal number of destinations to utilize for an event. In at least one embodiment, a user may specify how many destinations they would like to use for an event and the systems and methods described herein return the best solutions possible based on this user specification. In another embodiment, the solutions with the optimal number of destinations are returned)…0129: At step 1604, the system may identify the destination having the least average cost per resource, as set forth in Equation 6…0208: FIG. 28 shows illustrative view 2800 of information including halos 2802, 2804, 2806, 2808 and 2810 encircling destinations 2812, 2814, 2816, 2818 and 2820, respectively. The size of a halo represents the relative cumulative shadow cost that would be incurred by removing the corresponding destination from the solution set. View 2800 corresponds to a one-destination solution. Only the five least costly scenarios (“results”) are shown…0132: Each of successive iterations yields a higher total cost D.sub.T (set forth in Eq'n 7, below) than the previous scenario.”
Salchert and Waldeck are deemed to be analogous references as they are reasonably pertinent to each other and directed towards measuring, collecting, and analyzing information with a series of inputs to solve similar problems in the similar environments. Before the effective filing date of the claimed invention, it would have been obvious for one of ordinary skill in the art to have modified Salchert with the aforementioned teachings from Waldeck with a reasonable expectation of success, by adding steps that allow the software to select data with the motivation to more efficiently and accurately organize and analyze data [Waldeck 0045].
Salchert and Waldeck may not explicitly teach the following. However, Zhong teaches:
updatinq, by the one or more processors, a schedulinq system with the one or more data obiects; 0167-0170: “However, unassigned cells in the daily dispatching stage provide more freedom for the dispatch system to balance the workload and optimally construct daily routes…The methods and systems disclosed herein provide the tools for constructing a daily route plan for a service territory based on historical route data and the current daily demand. In one embodiment, as shown in FIG. 8, each cell 40 in a service territory 20 may be classified as a core cell 60, a flex zone cell 50, or a daily cell 70. Core cells 60 may be grouped together into a core area 100. The concept of using core areas 100 in a route planning process is an element of the present invention.”
Salchert, Waldeck, and Zhong are deemed to be analogous references as they are reasonably pertinent to each other and directed towards measuring, collecting, and analyzing information with a series of inputs to solve similar problems in the similar environments. Before the effective filing date of the claimed invention, it would have been obvious for one of ordinary skill in the art to have modified Salchert and Waldeck with the aforementioned teachings from Zhong with a reasonable expectation of success, by adding steps that allow the software to utilize data with the motivation to more efficiently and accurately organize and analyze information [Zhong 0069].
As per claim 2, Salchert and Waldeck teach all the limitations of claim 1.
In addition, Salchert teaches:
applying the ML model to the demand node data to cluster the plurality of demand nodes into the respective set of zones comprises: selecting a first subset of the plurality of demand nodes as a set of centroids or medoids, each centroid or medoid of the set of centroids or medoids corresponding to a respective zone of the respective set of zones, and assigning a second subset of the plurality of demand nodes to the respective set of zones based upon shortest distances to the set of centroids or medoids; and 0043-0051: “ selecting, from the map data in the array memory, a plurality of geographic units as different cluster starting units; for each of the different cluster starting units, calculating one or more nearest neighbor units, determining a shortest distance between non-clustered units among the nearest neighbor units that is less than or equal to a maximum allowed distance value, marking said non-clustered units having the shortest distance for clustering… Each of A, B, C, D is assigned to a relatively high-valued cell in each of four (4) quadrants of the map. FIG. 2 illustrates the map of FIG. 1 in which the high-valued cells are circled. Four high-value cells 202, 204, 206, 208 are defined. In one embodiment, four (4) initial territory definitions 210, 212, 214, 216 are assigned, each including only cells for which the assigned entity is closer than any other entity.”
Salchert and Waldeck may not explicitly teach the following. However, Zhong teaches:
determining the supply node allocations for the respective set of zones included in the zone configuration based on the the set of to the set of ; 0318-0319: “First, in one embodiment, the present invention includes a VRP solution method adapted for routing entire cells instead of individual stops. In one aspect, a cell may be treated mathematically as a large super-stop, having a location at the centroid of all stops within the cell and a service time equal to the time needed to serve all the stops within the cell including travel time between stops. [0319] For a route consisting of cells (1, 2, . . . , i, j, . . . , n), in that order. Cell u is an un-routed super-stop. The cost of inserting cell u between stops i and j may be expressed as: C(i,u,j)=D.sub.iu+D.sub.uj-D.sub.ij where D is the distance matrix among cells. If the insertion is not feasible, the insertion cost C is infinite. The cost C may be referred to as a cost constraint, in relation to the adapted VRP algorithm…0327: find a node tour that starts and ends at subset S.sub.0, that only has one node (the depot or hub 30), visits all nodes exactly once, and has a minimum total distance traveled.”
Salchert, Waldeck, and Zhong are deemed to be analogous references as they are reasonably pertinent to each other and directed towards measuring, collecting, and analyzing information with a series of inputs to solve similar problems in the similar environments. Before the effective filing date of the claimed invention, it would have been obvious for one of ordinary skill in the art to have modified Salchert and Waldeck with the aforementioned teachings from Zhong with a reasonable expectation of success, by adding steps that allow the software to utilize data with the motivation to more efficiently and accurately organize and analyze information [Zhong 0069].
As per claim 3, Salchert, Waldeck, and Zhong teach all the limitations of claim 1.
In addition, Waldeck teaches:
wherein the ML model comprises a k-means clustering mod; 0155: “At initial data load 2004, a K-means clustering algorithm is run on the latitude-longitude coordinates of attendee locations utilizing Haversine distance calculations…0100: consistent with step 502 (shown in FIG. 5), may apply k-means clustering to resources 304 to solve for and plot cluster means 602, 604 and 606..0093: The clusters may be determined using spatial k-means clustering…0093: The clusters may be determined using spatial k-means clustering.”
Salchert and Waldeck are deemed to be analogous references as they are reasonably pertinent to each other and directed towards measuring, collecting, and analyzing information with a series of inputs to solve similar problems in the similar environments. Before the effective filing date of the claimed invention, it would have been obvious for one of ordinary skill in the art to have modified Salchert with the aforementioned teachings from Waldeck with a reasonable expectation of success, by adding steps that allow the software to select data with the motivation to more efficiently and accurately organize and analyze data [Waldeck 0045].
As per claim 4, Salchert, Waldeck, and Zhong teach all the limitations of claim 1.
In addition, Salchert teaches:
wherein each zone configuration of the plurality of zone configurations consists of a different number of zones; 0072-0079: “assume that the territory alignment task requiring a machine solution is to assign the Zip codes regions of FIG. 11 among either three or four entities or sales reps… Based on the nineteen paths of FIG. 15, alignments or solutions having three territories or four territories may be formed. FIG. 16 illustrates the digital map of FIG. 15 in which three territories are defined.”
As per claim 5, Salchert, Waldeck, and Zhong teach all the limitations of claim 1.
Salchert and Waldeck may not explicitly teach the following. However, Zhong teaches:
verifying that an allocation of supply nodes to the respective set of zones does not exceed a maximum count for each supply node, wherein the maximum count is a maximum number of demand nodes that can be assigned to a single supply node; 0209: “a Generalized Assignment Problem (GAP) involves assigning tasks to agents. Each task must be assigned to one and only one agent. Each agent has a limited amount of capacity. An agent may have multiple tasks assigned to it, but the sum of the resource requirements for these tasks must not exceed the agent's capacity. The resource requirements of a particular task and the assignment cost depend on the agent who will perform the task…0218: for each destination node k there is a demand that must not exceed Q.sub.k units. The flow in each arc is restricted to integers, so they can be only 0 or 1. There is also a cost f.sub.ik and a multiplier .alpha..sub.ik for every arc, which respectively represent the cost and capacity requirement for assigning cell i to core area k. FIG. 17 shows the Non-linear GAP netform, where the costs are enclosed in boxes and the multipliers are enclosed in triangles…0194: the method of the present invention includes a primal stochastic program formulated to accomplish the stochastic Core Area Design model. The decision variables of the model are the following integer variables.”
Salchert, Waldeck, and Zhong are deemed to be analogous references as they are reasonably pertinent to each other and directed towards measuring, collecting, and analyzing information with a series of inputs to solve similar problems in the similar environments. Before the effective filing date of the claimed invention, it would have been obvious for one of ordinary skill in the art to have modified Salchert and Waldeck with the aforementioned teachings from Zhong with a reasonable expectation of success, by adding steps that allow the software to utilize data with the motivation to more efficiently and accurately organize and analyze information [Zhong 0069].
As per claim 6, Salchert, Waldeck, and Zhong teach all the limitations of claim 1.
Salchert and Waldeck may not explicitly teach the following. However, Zhong teaches:
verifying that an allocation of supply nodes to the respective set of zones equals or exceeds a minimum count for each supply node, wherein the minimum count is a minimum number of demand nodes that can be assigned to a single supply node; 0125: “the route planning system 10 of the present invention solves this problem by selecting a reference day on which the minimum number of drivers is available. Each driver is assigned a route on the reference day. For subsequent days, an attempt is first made to assign the same driver to the new route that has the most amount of territory overlap with the assigned route. The following steps illustrate an embodiment of a driver route assignment method: [0126] (1) Execute a route planning algorithm over the service territory 20 for each day during a reference period. [0127] (a) Determine the number of assigned routes needed for each day during the reference period…0320: the present invention includes a VRP solution method adapted for the fact that some of the cells are assigned as core cells 60 to a regular driver. The number of core cells k may be determined by the number of regular drivers or by the expected minimum number of drivers needed each day. Therefore, k partial routes may be used to serve as a starting point. The series of k partial routes may be referred to as a core constraint, in relation to the adapted VRP algorithm being formulated. The starting point of k partial routes is similar to the starting point for the parallel route construction heuristic described above. Accordingly, there is no need to run a sequential route construction heuristic to determine the number of routes.”
Salchert, Waldeck, and Zhong are deemed to be analogous references as they are reasonably pertinent to each other and directed towards measuring, collecting, and analyzing information with a series of inputs to solve similar problems in the similar environments. Before the effective filing date of the claimed invention, it would have been obvious for one of ordinary skill in the art to have modified Salchert and Waldeck with the aforementioned teachings from Zhong with a reasonable expectation of success, by adding steps that allow the software to utilize data with the motivation to more efficiently and accurately organize and analyze information [Zhong 0069].
As per claim 7, Salchert, Waldeck, and Zhong teach all the limitations of claim 1.
In addition, Salchert teaches:
determining, by the one or more processors and for one or more of the supply nodes, a zone assignment based on the particular zone configuration, wherein the zone assignment comprises a single zone of the plurality of respective zones assigned to each of the one or more supply nodes; and causing, by the one or more processors, a display to present a visual indication of the zone assignment; 0051: “ four (4) initial territory definitions 210, 212, 214, 216 are assigned, each including only cells for which the assigned entity is closer than any other entity, assuming the distance between all adjacent cells is the same. In this context, “closer” means fewer cells to travel. FIG. 2 represents an efficient territory alignment, if travel or distance is the sole criterion for determining efficiency. The hatched cells 218 are those which can be served by two or more reps with equal efficiency, which means they are as-yet undecided or unassigned…0048: the method may further comprise causing generating a digital graphical visual display of the territory data on a display device of a user computer that is communicatively coupled via a network…0087: ] Presentation instructions 1722, when used, are programmed to digitally render visual representations of the map data 1702, with or without metric data 1704, and/or territory map data, for visual presentation on a computer display device.”
As per claim 8, Salchert, Waldeck, and Zhong teach all the limitations of claim 1.
In addition, Waldeck teaches:
wherein determining the supply node allocations for the respective set of zones included in the zone configuration comprises minimizing a total cost for the zone configuration using an objective function; 0107: “The system use Equation 1, below, to calculate a total cost C.sub.Tj,i for each cluster-destination pair…0132: FIG. 17 shows a hypothetical plot showing increasing total cost with successive removal of D.sub.min. Each of successive iterations yields a higher total cost D.sub.T (set forth in Eq'n 7, below) than the previous scenario, indicating success of process 100. The system may select different destinations (save those removed as a D.sub.min) from one iteration to the next…0045: a custom optimization algorithm partitions the group to ensure the set of destinations in the result achieve the lowest possible cost while respecting the constraints of each destination (e.g. not sending 400 guests to a destination that may only accommodate 300). “
Salchert and Waldeck are deemed to be analogous references as they are reasonably pertinent to each other and directed towards measuring, collecting, and analyzing information with a series of inputs to solve similar problems in the similar environments. Before the effective filing date of the claimed invention, it would have been obvious for one of ordinary skill in the art to have modified Salchert with the aforementioned teachings from Waldeck with a reasonable expectation of success, by adding steps that allow the software to select data with the motivation to more efficiently and accurately organize and analyze data [Waldeck 0045].
Claims 9, 12, 15-17, 20, and 23-24 recite the system and CRM for performing parallel limitations of claims 1, 3-4, and 7-8 above. Thus, the same art and rationale apply.
Claims 10, 13-14, 18, and 21-22 recite the system and CRM for performing parallel limitations of claims 2 and 5-6 above. Thus, the same art and rationale apply.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
LE GOFF; Morvan. METHOD AND SYSTEM FOR SUPERVISING A HEALTH OF A SERVER INFRASTRUCTURE, .U.S. PGPub20200379529 The present technology relates to the field of data processing systems. In particular, the systems and methods for supervising a health of a server infrastructure.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any extension fee pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Arif Ullah, whose telephone number is (571) 270-0161. The examiner can normally be reached from Monday to Friday between 9 AM and 5:30 PM.
If any attempt to reach the examiner by telephone is unsuccessful, the examiner’s supervisor, Beth Boswell, can be reached at (571) 272-6737. The fax telephone numbers for this group are either (571) 273-8300 or (703) 872-9326 (for official communications including After Final communications labeled “Box AF”).
/Arif Ullah/
Primary Examiner, Art Unit 3625
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