Developing heuristic and meta-heuristic algorithms for the problem of joint order batching and collector routing in single and multiple-cross-aisle warehouses
Purpose: Organization of the order selection process is one of the most important issues in warehouse management, and combining several customer orders in one order can increase the efficiency of warehouse operations and better use of resources and labor. It also reduces the time of the order select...
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| Format: | Article |
| Language: | fas |
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Ayandegan Institute of Higher Education, Tonekabon,
2024-08-01
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| Series: | تصمیم گیری و تحقیق در عملیات |
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| Online Access: | https://www.journal-dmor.ir/article_199977_41f82c0285f8bc2086086b1c214193d5.pdf |
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| _version_ | 1832577848086364160 |
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| author | Zahra Shamlou Taha Keshavarz |
| author_facet | Zahra Shamlou Taha Keshavarz |
| author_sort | Zahra Shamlou |
| collection | DOAJ |
| description | Purpose: Organization of the order selection process is one of the most important issues in warehouse management, and combining several customer orders in one order can increase the efficiency of warehouse operations and better use of resources and labor. It also reduces the time of the order selection process and the distance traveled.Methodology: In this research, we have presented a method to solve the problem of order batching and collectors routing. A meta-heuristic based on the genetic algorithm is proposed in this research. For a more accurate comparison, in addition to the category number of common items, we also considered the percentage of common items in each order.Findings: The proposed method in this research has been compared with the combination of Nearest Neighbor (NN), Largest Gap, and S-shape algorithms. The test results on the random data sets have shown that the genetic algorithm provides fast and effective solutions. By evaluating the sensitivity analysis of the parameters, it was observed that the distance covered by the combined genetic method is better than the S-shape+Largest Gap+NN method.Originality/Value: In this article, the genetic algorithm is used for the problem of classification of joint orders and routing of collectors in warehouses at the same time. |
| format | Article |
| id | doaj-art-eb85110726834e85b593d7a2d26ea64c |
| institution | Kabale University |
| issn | 2538-5097 2676-6159 |
| language | fas |
| publishDate | 2024-08-01 |
| publisher | Ayandegan Institute of Higher Education, Tonekabon, |
| record_format | Article |
| series | تصمیم گیری و تحقیق در عملیات |
| spelling | doaj-art-eb85110726834e85b593d7a2d26ea64c2025-01-30T15:03:45ZfasAyandegan Institute of Higher Education, Tonekabon,تصمیم گیری و تحقیق در عملیات2538-50972676-61592024-08-019237138410.22105/dmor.2024.437683.1846199977Developing heuristic and meta-heuristic algorithms for the problem of joint order batching and collector routing in single and multiple-cross-aisle warehousesZahra Shamlou0Taha Keshavarz1Industrial Engineering Department Semnan University, Semnan, IranIndustrial Engineering Department Semnan University, Semnan, IranPurpose: Organization of the order selection process is one of the most important issues in warehouse management, and combining several customer orders in one order can increase the efficiency of warehouse operations and better use of resources and labor. It also reduces the time of the order selection process and the distance traveled.Methodology: In this research, we have presented a method to solve the problem of order batching and collectors routing. A meta-heuristic based on the genetic algorithm is proposed in this research. For a more accurate comparison, in addition to the category number of common items, we also considered the percentage of common items in each order.Findings: The proposed method in this research has been compared with the combination of Nearest Neighbor (NN), Largest Gap, and S-shape algorithms. The test results on the random data sets have shown that the genetic algorithm provides fast and effective solutions. By evaluating the sensitivity analysis of the parameters, it was observed that the distance covered by the combined genetic method is better than the S-shape+Largest Gap+NN method.Originality/Value: In this article, the genetic algorithm is used for the problem of classification of joint orders and routing of collectors in warehouses at the same time.https://www.journal-dmor.ir/article_199977_41f82c0285f8bc2086086b1c214193d5.pdfwarehouse managementorder batchingcollector routingsimilarity indexgenetic algorithm |
| spellingShingle | Zahra Shamlou Taha Keshavarz Developing heuristic and meta-heuristic algorithms for the problem of joint order batching and collector routing in single and multiple-cross-aisle warehouses تصمیم گیری و تحقیق در عملیات warehouse management order batching collector routing similarity index genetic algorithm |
| title | Developing heuristic and meta-heuristic algorithms for the problem of joint order batching and collector routing in single and multiple-cross-aisle warehouses |
| title_full | Developing heuristic and meta-heuristic algorithms for the problem of joint order batching and collector routing in single and multiple-cross-aisle warehouses |
| title_fullStr | Developing heuristic and meta-heuristic algorithms for the problem of joint order batching and collector routing in single and multiple-cross-aisle warehouses |
| title_full_unstemmed | Developing heuristic and meta-heuristic algorithms for the problem of joint order batching and collector routing in single and multiple-cross-aisle warehouses |
| title_short | Developing heuristic and meta-heuristic algorithms for the problem of joint order batching and collector routing in single and multiple-cross-aisle warehouses |
| title_sort | developing heuristic and meta heuristic algorithms for the problem of joint order batching and collector routing in single and multiple cross aisle warehouses |
| topic | warehouse management order batching collector routing similarity index genetic algorithm |
| url | https://www.journal-dmor.ir/article_199977_41f82c0285f8bc2086086b1c214193d5.pdf |
| work_keys_str_mv | AT zahrashamlou developingheuristicandmetaheuristicalgorithmsfortheproblemofjointorderbatchingandcollectorroutinginsingleandmultiplecrossaislewarehouses AT tahakeshavarz developingheuristicandmetaheuristicalgorithmsfortheproblemofjointorderbatchingandcollectorroutinginsingleandmultiplecrossaislewarehouses |