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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 05/29/2024 is in compliance with the provisions of 37 CFR 1.97 and have been entered into the record. Accordingly, the information disclosure statements are being considered by the examiner.
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 1-20 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 1-20 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 1-7), computer program product (claims 8-13), and system (claims 14-20) 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…to demand node data indicating locations of a plurality of demand nodes, wherein each zone configuration of the plurality of zone configurations includes a respective set of zones among a plurality of sets of zones; determining… a plurality of respective costs for the plurality of zone configurations, wherein determining the plurality of respective costs for each zone configuration of the plurality of zone configurations comprises: determining supply node allocations for the respective set of zones included in the zone configuration based on times or 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, and determining a respective cost, of the plurality of respective costs, for the zone configuration based on (i) the times or distances and (ii) the supply node allocations; selecting…a particular zone configuration, from among the plurality of zone configurations, based on the plurality of respective costs; and 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… in a memory, by the one or more processors…; 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… in a memory, by the one or more processors…; 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, 3-4, 7-9, 12, 15-17, 20, and 23-24 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. PGPub 20120203596 (hereinafter “Guthridge”) et al.
As per claim 1, Salchert teaches a computer-implemented method comprising:
generating, by one or more processors, a plurality of zone configurations, at least by applying a machine learning (ML) model to demand node data indicating locations of a plurality of demand nodes, wherein each zone configuration of the plurality of zone configurations includes a respective set of zones among a plurality of sets of zones; 0041: “With digitally stored geographical maps, programmed algorithms can calculate a plurality of territories within a map, the territories being balanced with respect to metric data that is associated with units of the map, using channel flow-based principles of the Constructal Law…0072-0079: For purposes of illustrating a clear example, 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. Embodiments also can be used to determine if there is a better way to align an existing set of sales reps or entities…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. In an embodiment, rendering 1200 is updated, in FIG. 16, to include coded representations of paths; a key table 1602 is visually displayed near the map and comprises a key column 1604 of matching key values corresponding to paths, a territory column 1605 identifying path names or numbers, and a decile column 1606 specifying corresponding sums of units on each path.”
determining, by the one or more processors, a plurality of respective costs for the plurality of zone configurations, wherein determining the plurality of respective costs for each zone configuration of the plurality of zone configurations comprises: 0062-0068: “FIG. 7 illustrates the map of FIG. 5, FIG. 6 with circles denoting twenty section centers. Three section centers 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… an optimization step may be executed to scan for possible improvements to the alignment. Optimization may be programmed as a balanced tradeoff between neighboring territories. The sections should remain intact, and the territories' cumulative values should remain relatively equal. In an embodiment, imbalance could be allowed optionally if an improvement in efficiency would be achieved. FIG. 8 illustrates the map of FIG. 7 after applying an optimization step. In the embodiment of FIG. 8, one section of the lower-right territory 602 has been shifted to the upper-right territory 504. The upper-right territory 504 continues to have a long-haul total of six, while the lower-right territory 602 has a long-haul total that drops from seven to six. Visually, these two territories 504, 602 may look worse, but only due to human aesthetic bias. There is nothing inherently inefficient about the revised territory shapes, from a Constructal flow perspective. Applying optimization to the left-side territories 604, 606 will not yield an improvement without worsening the efficiency of the overall alignment of all territories.”
determining supply node allocations for the respective set of zones included in the zone configuration based on times or 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, and determining a respective cost, of the plurality of respective costs, for the zone configuration based on (i) the times or distances and (ii) the supply node allocations; 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.”
and storing in a memory, by the one or more processors, one or more data objects representing the particular zone configuration; 0043 and 0084: “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…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. In an embodiment, the foregoing elements are programmed to solve the technical problem of how to dynamically calculate and update balanced territories consisting of one or more units of a digital map in response to changes in metric values associated with the units.”
Salchert may not explicitly teach the following. However, Waldeck teaches:
selecting, by the one or more processors, a particular zone configuration, from among the plurality of zone configurations, based on the plurality of respective costs; 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)…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.”
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 3, Salchert and Waldeck 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 and Waldeck 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 7, Salchert and Waldeck 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 and Waldeck 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 2, 5-6, 10, 13-14, 18, and 21-22 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. PGPub 20100088146 (hereinafter “Zhong”) et al.
As per claim 2, Salchert and Waldeck teach all the limitations of claim 1.
Salchert and Waldeck may not explicitly teach the following. However, Zhong teaches:
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;0069: “Instead of using the centroid-to-centroid distance between cells to estimate the cell-to-cell distance, one embodiment of the present invention includes the following distance model…0318-0319: , 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. 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.”
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 5, Salchert and Waldeck 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 and Waldeck 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].
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.
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
Prosecution Insights