Metaheuristic Algorithms Based on Compromise Programming for the Multi-Objective Urban Shipment Problem
The Vehicle Routing Problem (VRP) and its variants are found in many fields, especially logistics. In this study, we introduced an adaptive method to a complex VRP. It combines multi-objective optimization and several forms of VRPs with practical requirements for an urban shipment system. The optimi...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-03-01
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| Series: | Entropy |
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| Online Access: | https://www.mdpi.com/1099-4300/24/3/388 |
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| author | Tung Son Ngo Jafreezal Jaafar Izzatdin Abdul Aziz Muhammad Umar Aftab Hoang Giang Nguyen Ngoc Anh Bui |
| author_facet | Tung Son Ngo Jafreezal Jaafar Izzatdin Abdul Aziz Muhammad Umar Aftab Hoang Giang Nguyen Ngoc Anh Bui |
| author_sort | Tung Son Ngo |
| collection | DOAJ |
| description | The Vehicle Routing Problem (VRP) and its variants are found in many fields, especially logistics. In this study, we introduced an adaptive method to a complex VRP. It combines multi-objective optimization and several forms of VRPs with practical requirements for an urban shipment system. The optimizer needs to consider terrain and traffic conditions. The proposed model also considers customers’ expectations and shipper considerations as goals, and a common goal such as transportation cost. We offered compromise programming to approach the multi-objective problem by decomposing the original multi-objective problem into a minimized distance-based problem. We designed a hybrid version of the genetic algorithm with the local search algorithm to solve the proposed problem. We evaluated the effectiveness of the proposed algorithm with the Tabu Search algorithm and the original genetic algorithm on the tested dataset. The results show that our method is an effective decision-making tool for the multi-objective VRP and an effective solver for the new variation of VRP. |
| first_indexed | 2024-03-09T19:52:04Z |
| format | Article |
| id | doaj.art-42bac29456574daf887ebd7741155d2a |
| institution | Directory Open Access Journal |
| issn | 1099-4300 |
| language | English |
| last_indexed | 2024-03-09T19:52:04Z |
| publishDate | 2022-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Entropy |
| spelling | doaj.art-42bac29456574daf887ebd7741155d2a2023-11-24T01:07:41ZengMDPI AGEntropy1099-43002022-03-0124338810.3390/e24030388Metaheuristic Algorithms Based on Compromise Programming for the Multi-Objective Urban Shipment ProblemTung Son Ngo0Jafreezal Jaafar1Izzatdin Abdul Aziz2Muhammad Umar Aftab3Hoang Giang Nguyen4Ngoc Anh Bui5Department of Computer and Information Sciences, Universiti Teknologi PETRONAS, Seri Iskandar 32610, MalaysiaDepartment of Computer and Information Sciences, Universiti Teknologi PETRONAS, Seri Iskandar 32610, MalaysiaDepartment of Computer and Information Sciences, Universiti Teknologi PETRONAS, Seri Iskandar 32610, MalaysiaDepartment of Computer Science, National University of Computer and Emerging Sciences, Chiniot-Faisalabad Campus, Chiniot 35400, PakistanInformation and Communication Department, FPT University, Hanoi 10000, VietnamInformation and Communication Department, FPT University, Hanoi 10000, VietnamThe Vehicle Routing Problem (VRP) and its variants are found in many fields, especially logistics. In this study, we introduced an adaptive method to a complex VRP. It combines multi-objective optimization and several forms of VRPs with practical requirements for an urban shipment system. The optimizer needs to consider terrain and traffic conditions. The proposed model also considers customers’ expectations and shipper considerations as goals, and a common goal such as transportation cost. We offered compromise programming to approach the multi-objective problem by decomposing the original multi-objective problem into a minimized distance-based problem. We designed a hybrid version of the genetic algorithm with the local search algorithm to solve the proposed problem. We evaluated the effectiveness of the proposed algorithm with the Tabu Search algorithm and the original genetic algorithm on the tested dataset. The results show that our method is an effective decision-making tool for the multi-objective VRP and an effective solver for the new variation of VRP.https://www.mdpi.com/1099-4300/24/3/388multi objective optimizationVRPcompromise programminggenetic algorithmlocal searchTabu search |
| spellingShingle | Tung Son Ngo Jafreezal Jaafar Izzatdin Abdul Aziz Muhammad Umar Aftab Hoang Giang Nguyen Ngoc Anh Bui Metaheuristic Algorithms Based on Compromise Programming for the Multi-Objective Urban Shipment Problem Entropy multi objective optimization VRP compromise programming genetic algorithm local search Tabu search |
| title | Metaheuristic Algorithms Based on Compromise Programming for the Multi-Objective Urban Shipment Problem |
| title_full | Metaheuristic Algorithms Based on Compromise Programming for the Multi-Objective Urban Shipment Problem |
| title_fullStr | Metaheuristic Algorithms Based on Compromise Programming for the Multi-Objective Urban Shipment Problem |
| title_full_unstemmed | Metaheuristic Algorithms Based on Compromise Programming for the Multi-Objective Urban Shipment Problem |
| title_short | Metaheuristic Algorithms Based on Compromise Programming for the Multi-Objective Urban Shipment Problem |
| title_sort | metaheuristic algorithms based on compromise programming for the multi objective urban shipment problem |
| topic | multi objective optimization VRP compromise programming genetic algorithm local search Tabu search |
| url | https://www.mdpi.com/1099-4300/24/3/388 |
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