Modified mixed-dimension chaotic particle swarm optimization for liner route planning with empty container repositioning

M. Z. Yu; Z. C. Chen; L. Chen; QU, R.; Niu, B.

Abstract

Empty container repositioning has become one of the important issues in ocean shipping industry. Researchers often solve these problems using linear programming or simulation. For large-scale problems, heuristic algorithms showed to be preferable due to their flexibility and scalability. In this paper we consider large-scale the liner routing planning problem with empty container repositioning (LRPECR) model where allocation strategies and liner routes need to be designed to allocate empty containers from the supply ports to the demand ports. According to the characteristics of the LRPECR model, we combine the path of the ship to the algorithm encoding, set up the fitness function that minimizes the total cost, and use a modified Particle Swarm Optimization (PSO) algorithm to search for optimal shipping routes in a feasible space iteratively. The modified PSO combines chaotic theory and Cat map to overcome the defect of traditional PSO. In addition, we perform chaotic search in different dimensions to enhance the search accuracy of the algorithm that means the increased diversity of search scope. In order to validate our algorithm, standard PSO and GA are chosen as the compared algorithms. Through numerical studies based on real applications, the experimental results demonstrate that the modified PSO is able to find preferable solutions efficiently for the empty container repositioning problem.

Citation

M. Z. Yu, Z. C. Chen, L. Chen, QU, R., & Niu, B. (2018). Modified mixed-dimension chaotic particle swarm optimization for liner route planning with empty container repositioning. https://doi.org/10.1007/978-981-13-2829-9_27

• Conference Name: The 13th International Conference on Bio-inspired Computing: Theories and Applications
• Conference Location: Beijing, China
• Start Date: Nov 2, 2018
• End Date: Nov 4, 2018
• Acceptance Date: Aug 19, 2018
• Online Publication Date: Oct 6, 2018
• Publication Date: Oct 6, 2018
• Deposit Date: Nov 20, 2018
• Publicly Available Date: Nov 20, 2018
• Publisher: Springer Verlag
• Pages: 296-307
• Series Title: Communications in Computer and Information Science
• Series Number: 952
• ISBN: 9789811328282
• DOI: https://doi.org/10.1007/978-981-13-2829-9_27
• Public URL: https://nottingham-repository.worktribe.com/output/1283896
• Publisher URL: https://link.springer.com/chapter/10.1007/978-981-13-2829-9_27
• Additional Information: The final authenticated publication is available online at https://doi.org/[insert DOI]”.