Improved Ant Colony Optimization for Seafood Product Delivery Routing Problem

  • Baozhen Yao School of Automotive Engineering, Dalian University of Technology Dalian, 116024, China
  • Ping Hu School of Automotive Engineering, Dalian University of Technology Dalian, 116024, China
  • Mingheng Zhang School of Automotive Engineering, Dalian University of Technology Dalian, 116024, China
  • Xiaomei Tian CTS International Logistics Corporation Limited Dalian, 116001, China
Keywords: Seafood Product Delivery Routing Problem, Multi-Depot Open Vehicle Routing Problem, Ant Colony Optimization, Adaptive Strategy, Crossover Operation

Abstract

This paper deals with a real-life vehicle delivery routing problem, which is a seafood product delivery routing problem. Considering the features of the seafood product delivery routing problem, this paper formulated this problem as a multi-depot open vehicle routing problem. Since the multi-depot open vehicle routing problem is a very complex problem, a method is used to reduce the complexity of the problem by changing the multi-depot open vehicle routing problem into an open vehicle routing problem with a dummy central depot in this paper. Then, ant colony optimization is used to solve the problem. To improve the performance of the algorithm, crossover operation and some adaptive strategies are used. Finally, the computational results for the benchmark problems of the multi-depot vehicle routing problem indicate that the proposed ant colony optimization is an effective method to solve the multi-depot vehicle routing problem. Furthermore, the computation results of the seafood product delivery problem from Dalian, China also suggest that the proposed ant colony optimization is feasible to solve the seafood product delivery routing problem.

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How to Cite
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Yao B, Hu P, Zhang M, Tian X. Improved Ant Colony Optimization for Seafood Product Delivery Routing Problem. Promet [Internet]. 1 [cited 2024Apr.25];26(1):1-10. Available from: http://traffic.fpz.hr/index.php/PROMTT/article/view/1478
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