Multi-objective shipment consolidation and dispatching problem
In recent years, with the increase in global production and demand, transportation problems have become a widely studied area, and studies focus on providing high-quality service at the lowest cost. This study considers a bi-objective shipment consolidation and dispatching problem with the objective...
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| Published in: | Computers & operations research Vol. 169; p. 106728 |
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| Main Authors: | , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Elsevier Ltd
01.09.2024
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| Subjects: | |
| ISSN: | 0305-0548, 1873-765X |
| Online Access: | Get full text |
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| Summary: | In recent years, with the increase in global production and demand, transportation problems have become a widely studied area, and studies focus on providing high-quality service at the lowest cost. This study considers a bi-objective shipment consolidation and dispatching problem with the objectives of minimizing the total cost and the total distance. To the best of our knowledge, this is the first study to include both objectives in this problem. Additionally, different from the literature, where usually predefined routes are assumed, we incorporate the routing decisions in our model. In order to create a non-dominated solution set, a multi-objective mixed integer linear programming model is developed and augmented ϵ-constraint method is used to generate the non-dominated frontier. However, this approach is not capable of finding the non-dominated solution set in a reasonable time, even for small-sized instances, and therefore, we propose a multi-objective variable neighborhood search heuristic. To measure the performance of the proposed approach, a computational experiment is conducted on randomly generated instances available in the literature. The experimental results indicate that the multi-objective variable neighborhood search heuristic performs efficiently in reasonable time.
•This paper considers a bi-objective shipment consolidation and dispatching problem.•The objectives are to minimize the total cost and total distance traveled.•Augmented epsilon-constraint method is used to generate the efficient frontier.•VNS algorithm is developed to approximate the efficient frontier. |
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| ISSN: | 0305-0548 1873-765X |
| DOI: | 10.1016/j.cor.2024.106728 |