Modified Differential Evolution Algorithm for a Transportation Software Application
This research developed a solution approach that is a combination of a web application and the modified differential evolution (MDE) algorithm, aimed at solving a real-time transportation problem. A case study involving an inbound transportation problem in a company that has to plan the direct shipp...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2019-10-01
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| Series: | Journal of Open Innovation: Technology, Market and Complexity |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2199-8531/5/4/84 |
| _version_ | 1827612685091471360 |
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| author | Naratip Supattananon Raknoi Akararungruangkul |
| author_facet | Naratip Supattananon Raknoi Akararungruangkul |
| author_sort | Naratip Supattananon |
| collection | DOAJ |
| description | This research developed a solution approach that is a combination of a web application and the modified differential evolution (MDE) algorithm, aimed at solving a real-time transportation problem. A case study involving an inbound transportation problem in a company that has to plan the direct shipping of a finished product to be collected at the depot where the vehicles are located is presented. In the newly designed transportation plan, a vehicle will go to pick up the raw material required by a certain production plant from the supplier to deliver to the production plant in a manner that aims to reduce the transportation costs for the whole system. The reoptimized routing is executed when new information is found. The information that is updated is obtained from the web application and the reoptimization process is executed using the MDE algorithm developed to provide the solution to the problem. Generally, the original DE comprises of four steps: (1) randomly building the initial set of the solution, (2) executing the mutation process, (3) executing the recombination process, and (4) executing the selection process. Originally, for the selection process in DE, the algorithm accepted only the better solution, but in this paper, four new selection formulas are presented that can accept a solution that is worse than the current best solution. The formula is used to increase the possibility of escaping from the local optimal solution. The computational results show that the MDE outperformed the original DE in all tested instances. The benefit of using real-time decision-making is that it can increase the company’s profit by 5.90% to 6.42%. |
| first_indexed | 2024-03-09T08:26:49Z |
| format | Article |
| id | doaj.art-940d9464a9be4783b4e70464770aac41 |
| institution | Directory Open Access Journal |
| issn | 2199-8531 |
| language | English |
| last_indexed | 2024-03-09T08:26:49Z |
| publishDate | 2019-10-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of Open Innovation: Technology, Market and Complexity |
| spelling | doaj.art-940d9464a9be4783b4e70464770aac412023-12-02T21:02:02ZengElsevierJournal of Open Innovation: Technology, Market and Complexity2199-85312019-10-01548410.3390/joitmc5040084joitmc5040084Modified Differential Evolution Algorithm for a Transportation Software ApplicationNaratip Supattananon0Raknoi Akararungruangkul1Department of Industrial Engineering, Faculty of Engineering, KhonKaen University, KhonKaen 40000, ThailandDepartment of Industrial Engineering, Faculty of Engineering, KhonKaen University, KhonKaen 40000, ThailandThis research developed a solution approach that is a combination of a web application and the modified differential evolution (MDE) algorithm, aimed at solving a real-time transportation problem. A case study involving an inbound transportation problem in a company that has to plan the direct shipping of a finished product to be collected at the depot where the vehicles are located is presented. In the newly designed transportation plan, a vehicle will go to pick up the raw material required by a certain production plant from the supplier to deliver to the production plant in a manner that aims to reduce the transportation costs for the whole system. The reoptimized routing is executed when new information is found. The information that is updated is obtained from the web application and the reoptimization process is executed using the MDE algorithm developed to provide the solution to the problem. Generally, the original DE comprises of four steps: (1) randomly building the initial set of the solution, (2) executing the mutation process, (3) executing the recombination process, and (4) executing the selection process. Originally, for the selection process in DE, the algorithm accepted only the better solution, but in this paper, four new selection formulas are presented that can accept a solution that is worse than the current best solution. The formula is used to increase the possibility of escaping from the local optimal solution. The computational results show that the MDE outperformed the original DE in all tested instances. The benefit of using real-time decision-making is that it can increase the company’s profit by 5.90% to 6.42%.https://www.mdpi.com/2199-8531/5/4/84vehicle dispatching probleminbound transportation problemmodified differential evolution algorithm |
| spellingShingle | Naratip Supattananon Raknoi Akararungruangkul Modified Differential Evolution Algorithm for a Transportation Software Application Journal of Open Innovation: Technology, Market and Complexity vehicle dispatching problem inbound transportation problem modified differential evolution algorithm |
| title | Modified Differential Evolution Algorithm for a Transportation Software Application |
| title_full | Modified Differential Evolution Algorithm for a Transportation Software Application |
| title_fullStr | Modified Differential Evolution Algorithm for a Transportation Software Application |
| title_full_unstemmed | Modified Differential Evolution Algorithm for a Transportation Software Application |
| title_short | Modified Differential Evolution Algorithm for a Transportation Software Application |
| title_sort | modified differential evolution algorithm for a transportation software application |
| topic | vehicle dispatching problem inbound transportation problem modified differential evolution algorithm |
| url | https://www.mdpi.com/2199-8531/5/4/84 |
| work_keys_str_mv | AT naratipsupattananon modifieddifferentialevolutionalgorithmforatransportationsoftwareapplication AT raknoiakararungruangkul modifieddifferentialevolutionalgorithmforatransportationsoftwareapplication |