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 .
Election/Restrictions
Claim 13 and 14 are withdrawn from further consideration pursuant to 37 CFR 1.142(b) as being drawn to a nonelected invention, there being no allowable generic or linking claim. Election was made without traverse in the reply filed on 1/26/26.
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.
Claim(s) 1-12 is/are directed to statutory methods under Step 1 of the eligibility analysis. However, the claims are further directed toward a judicial exception under Step 2A Prong One of the eligibility analysis, namely an abstract idea. Under Step 2A Prong Two of the eligibility analysis, the claim(s) does/do not include additional elements to integrate the exception into a practical application of that exception. Under Step 2B of the eligibility analysis, the claims are not sufficient to amount to significantly more than the judicial exception because nothing in the asserted claims purports to improve the functioning of the computer itself or effect an improvement in any other technology or technical field. The claim(s) is/are directed to the abstract idea of “a solution selection step of comparing suitabilities of the plurality of picking job arrays with each other and updating a picking job array having the highest suitability as a solution”. This falls under MPEP 2106.04(a)(2), Abstract Idea Groupings, I. MATHEMATICAL CONCEPTS, A. Mathematical Relationships, “iv. organizing information and manipulating information through mathematical correlations, Digitech Image Techs., LLC v. Electronics for Imaging, Inc., 758 F.3d 1344, 1350, 111 USPQ2d 1717, 1721 (Fed. Cir. 2014). The patentee in Digitech claimed methods of generating first and second data by taking existing information, manipulating the data using mathematical functions, and organizing this information into a new form. The court explained that such claims were directed to an abstract idea because they described a process of organizing information through mathematical correlations, like Flook's method of calculating using a mathematical formula. 758 F.3d at 1350, 111 USPQ2d at 1721”.
Here the claims recite a number of abstract mathematical concepts used to compare and select such as: sum of distances traveled between locations; locations of the goods are visited in the determined sequence is calculated by referencing distance matrix data; calculating, by the employee module, suitability of the second array; calculating, by the onlooker module, suitability of the fourth array; re-executed when the number of elements exchanged in the first array or second array is less than a value of (a total number of orders x the exchange ratio); the onlooker module executes any one of a roulette wheel selection method performs a Monte Carlo method, a ranking-based selection method, a stochastic universal sampling method, and a tournament selection method; higher than the suitability of the solution; exceeds a maximum number of update attempts; and when the number of executions of the solution selection step exceeds a maximum number of executions of the solution selection step; etc.
The additional element(s) or combination of elements in the claim(s) other than the abstract idea per se, i.e. medium, storage, alert, etc., amount(s) to no more than implementing the abstract idea on a generic computer system, (see MPEP 2106.04(a)(2)(III)(C)(1)) . Because a judicial exception is not eligible subject matter, if there are no additional claim elements besides the judicial exception, or if the additional claim elements merely recite another judicial exception, that is insufficient to integrate the judicial exception into a practical application. See, e.g., RecogniCorp, LLC v. Nintendo Co., 855 F.3d 1322, 1327, 122 USPQ2d 1377 (Fed. Cir. 2017) ("Adding one abstract idea (math) to another abstract idea (encoding and decoding) does not render the claim non-abstract"). Therefore, the claim(s) are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1-12 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Singh et al., US 20210387805 A1.
1. (Original) A method for organizing logistics picking jobs, the method comprising:
a source initialization step of generating a plurality of picking job arrays, (see Singh, ¶ 8)(Order grouping and associated product picking according to currently used order grouping strategies is illustrated in FIG. 2, where an array of six product storage aisles (Aisle 1-Aisle 6) are arranged within a warehouse), whose elements are set as random picking jobs, (see Singh, ¶ 6-7)(randomized order allocation); and
a solution selection step of comparing suitabilities of the plurality of picking job arrays with each other and updating a picking job array having the highest suitability as a solution, (see Singh, Abstract)(order allocation optimization and/or order grouping optimization that are individually or collectively usable to allocate and group warehouse orders in a manner that minimizes picker travel and maximizes labor productivity). Grouping an order in a manner that minimizes picker travel is considered to be the same as “comparing suitabilities of the plurality of picking job arrays” and “updating a picking job array having the highest suitability”.
2. (Original) The method for claim 1, wherein indices of the respective picking job arrays correspond to orders, and the elements correspond to the picking jobs for handling the orders, (see Singh, ¶ 8).
3. (Original) The method for claim 2, wherein the number of orders handled by each of a plurality of picking jobs is same as each other, or the number of orders handled by each picking job except for one picking job is same as each other, (see Singh, ¶ 84)(The similarity between the pick locations of the current task and those of a task associated with another given order may then be calculated).
4. (Original) The method for claim 1, wherein each suitability is a sum of distances traveled between locations in order to pick goods included in the orders, (see Singh, ¶ 86)(For warehouses where pickers pick multiple orders at a time, order grouping optimization attempts to minimize the picker travel distance by generating pick assignments (each of which contains multiple orders) whose items are located as close as possible to each other).
5. (Original) The method for claim 4, wherein location information about the goods to be picked for each picking job is obtained by referencing goods location data, a sequence of visiting the locations of the goods is determined by referencing location ranking data, and the distances traveled when the locations of the goods are visited in the determined sequence is calculated by referencing distance matrix data, (see Singh, ¶ 84).
6. (Original) The method for claim 1, wherein the solution selection step comprises: assigning a first array which is a picking job array to an employee module; searching for, by the employee module, a second array adjacent to the first array; calculating, by the employee module, suitability of the second array and transmitting one array having higher suitability from among the first array and second array to an onlooker module; probabilistically selecting one of a plurality of arrays received by the onlooker module; searching for a fourth array adjacent to a third array probabilistically selected by the onlooker module; calculating, by the onlooker module, suitability of the fourth array and selecting one array having higher suitability from among the third array and fourth array; and updating the solution as the selected array when the suitability of the array selected by the onlooker module is higher than the suitability of the solution, (see Singh, ¶ 82)(The order grouping optimization process may consider that if a picker travels from a first aisle to a second aisle, picking additional items that are located within the two aisles will only increase the vertical distance traveled by the picker. On the other hand, picking additional items that are located outside of the two aisles (i.e., in another aisle) will increase both the vertical and horizontal distance traveled by the picker). In this case each aisle to be picked can be considered to be an “array” as claimed.
7. (Original) The method for claim 6, wherein the searching for the second array adjacent to the first array or the searching for of the fourth array adjacent to the third array comprises: a first step of randomly setting an exchange ratio; a second step of searching for a second order whose goods list is same as or similar to that of a first order corresponding to an index selected in the first array or second array; and a third step of exchanging a picking job of the first order and a picking job of the second order, and the second step and third step are re-executed when the number of elements exchanged in the first array or second array is less than a value of (a total number of orders x the exchange ratio), (see Singh, ¶ 84)(The similarity between the pick locations of the current task and those of a task associated with another given order may then be calculated).
8. (Original) The method for claim 6, wherein the probabilistically selecting of one of the plurality of arrays received by the onlooker module executes any one of a roulette wheel selection method performs a Monte Carlo method, a ranking-based selection method, a stochastic universal sampling method, and a tournament selection method, (see Singh, ¶ 85)(Utilizing such a parameter allows for assessment of the tradeoff between picking more units and the resultant increase in the travel path of the picker).
9. (Original) The method for claim 6, wherein the solution selection step increases the number of update attempts by one when the suitability of the array selected by the onlooker module is not higher than the suitability of the solution, (see Singh, ¶ 119)(Any time a new order is added to the current pick assignment, the vector used to calculate the additional travel distance required for any new location visit resulting from adding the new order is updated).
10. (Original) The method for claim 1, further comprising: a source re-search step of generating the plurality of picking job arrays whose elements are set as the random picking jobs when the number of update attempts exceeds a maximum number of update attempts , (see Singh, ¶ 119)(Any time a new order is added to the current pick assignment, the vector used to calculate the additional travel distance required for any new location visit resulting from adding the new order is updated).
11. (Original) The method for claim 10, wherein the source re-search step transmits an instruction for the onlooker module to cause a scout module to generate the plurality of picking job arrays whose elements are set as the random picking jobs when the number of update attempts exceeds the maximum number of update attempts, (see Singh, ¶ 119)(Any time a new order is added to the current pick assignment, the vector used to calculate the additional travel distance required for any new location visit resulting from adding the new order is updated).
12. (Original) The method for claim 1, wherein, when the number of executions of the solution selection step exceeds a maximum number of executions of the solution selection step, the solution is output, and when not, the solution selection step is executed again, (see Singh, ¶ 83, 86)(the calibration vector simulates the increased travel distance… to minimize the picker travel distance by generating pick assignments (each of which contains multiple orders) whose items are located as close as possible to each other). The simulation is considered to be a form of executing and/or re-executing a solution selection step.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure: KR 20240050596 A, US 20210110334 A1, US 20250061396 A1.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to RUSSELL S GLASS whose telephone number is (571)272-7285. The examiner can normally be reached M-F, 9-5.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, FLORIAN ZEENDER can be reached at 571-272-6790. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/RUSSELL S GLASS/Primary Examiner, Art Unit 3627