A new efficient genetic algorithm-Taguchi-based approach for multi-period inventory routing problem
The inventory routing problem arises from the combination of the vehicle routing problem and the vendor-managed inventory problem. In this paper, we present a mathematical model and a novel genetic algorithm for solving the multi-period inventory routing problem. The objective is to supply products...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Ayandegan Institute of Higher Education,
2023-12-01
|
| Series: | International Journal of Research in Industrial Engineering |
| Subjects: | |
| Online Access: | https://www.riejournal.com/article_184195_90b682ec7f859711f76fb0cb6ca7559a.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832577770853498880 |
|---|---|
| author | Amin Farahbakhsh Amir Saman Kheirkhah |
| author_facet | Amin Farahbakhsh Amir Saman Kheirkhah |
| author_sort | Amin Farahbakhsh |
| collection | DOAJ |
| description | The inventory routing problem arises from the combination of the vehicle routing problem and the vendor-managed inventory problem. In this paper, we present a mathematical model and a novel genetic algorithm for solving the multi-period inventory routing problem. The objective is to supply products to scattered customers within a given time horizon while managing customer inventories to avoid shortages and minimize total inventory and transportation costs. To represent solutions for this problem, we introduce a new chromosomal structure. This structure offers simplicity in encoding and decoding solutions, maintains feasibility after crossover and mutation operations, addresses both routing and inventory management in a single step, and consolidates information about each solution method comprehensively. The algorithm parameters, including crossover and mutation rates, population size, number of iterations, and selection pressure, are fine-tuned using the Taguchi method. To assess algorithm efficiency, we utilize standard instances from the literature. Our results demonstrate that the proposed algorithm performs favorably compared to previous approaches. |
| format | Article |
| id | doaj-art-d0766b86be3646e0a14a70d4fe69b960 |
| institution | Kabale University |
| issn | 2783-1337 2717-2937 |
| language | English |
| publishDate | 2023-12-01 |
| publisher | Ayandegan Institute of Higher Education, |
| record_format | Article |
| series | International Journal of Research in Industrial Engineering |
| spelling | doaj-art-d0766b86be3646e0a14a70d4fe69b9602025-01-30T15:10:04ZengAyandegan Institute of Higher Education,International Journal of Research in Industrial Engineering2783-13372717-29372023-12-0112439741310.22105/riej.2023.403685.1387184195A new efficient genetic algorithm-Taguchi-based approach for multi-period inventory routing problemAmin Farahbakhsh0Amir Saman Kheirkhah1Department of Industrial Engineering, Faculty of Engineering, Bu-Ali Sina University, Hamedan, Iran.Department of Industrial Engineering, Faculty of Engineering, Bu-Ali Sina University, Hamedan, Iran.The inventory routing problem arises from the combination of the vehicle routing problem and the vendor-managed inventory problem. In this paper, we present a mathematical model and a novel genetic algorithm for solving the multi-period inventory routing problem. The objective is to supply products to scattered customers within a given time horizon while managing customer inventories to avoid shortages and minimize total inventory and transportation costs. To represent solutions for this problem, we introduce a new chromosomal structure. This structure offers simplicity in encoding and decoding solutions, maintains feasibility after crossover and mutation operations, addresses both routing and inventory management in a single step, and consolidates information about each solution method comprehensively. The algorithm parameters, including crossover and mutation rates, population size, number of iterations, and selection pressure, are fine-tuned using the Taguchi method. To assess algorithm efficiency, we utilize standard instances from the literature. Our results demonstrate that the proposed algorithm performs favorably compared to previous approaches.https://www.riejournal.com/article_184195_90b682ec7f859711f76fb0cb6ca7559a.pdfinventory routing problemgenetic algorithmmetaheuristicoptimization |
| spellingShingle | Amin Farahbakhsh Amir Saman Kheirkhah A new efficient genetic algorithm-Taguchi-based approach for multi-period inventory routing problem International Journal of Research in Industrial Engineering inventory routing problem genetic algorithm metaheuristic optimization |
| title | A new efficient genetic algorithm-Taguchi-based approach for multi-period inventory routing problem |
| title_full | A new efficient genetic algorithm-Taguchi-based approach for multi-period inventory routing problem |
| title_fullStr | A new efficient genetic algorithm-Taguchi-based approach for multi-period inventory routing problem |
| title_full_unstemmed | A new efficient genetic algorithm-Taguchi-based approach for multi-period inventory routing problem |
| title_short | A new efficient genetic algorithm-Taguchi-based approach for multi-period inventory routing problem |
| title_sort | new efficient genetic algorithm taguchi based approach for multi period inventory routing problem |
| topic | inventory routing problem genetic algorithm metaheuristic optimization |
| url | https://www.riejournal.com/article_184195_90b682ec7f859711f76fb0cb6ca7559a.pdf |
| work_keys_str_mv | AT aminfarahbakhsh anewefficientgeneticalgorithmtaguchibasedapproachformultiperiodinventoryroutingproblem AT amirsamankheirkhah anewefficientgeneticalgorithmtaguchibasedapproachformultiperiodinventoryroutingproblem AT aminfarahbakhsh newefficientgeneticalgorithmtaguchibasedapproachformultiperiodinventoryroutingproblem AT amirsamankheirkhah newefficientgeneticalgorithmtaguchibasedapproachformultiperiodinventoryroutingproblem |