Route Optimization of Aquatic Product Transportation Based on an Improved Ant Colony Algorithm

Abstract

In this paper, the time window in which aquatic products must be delivered and the uncertainty of road conditions that affect the time at which customers are able to receive the goods are added as constraints in the optimization model of the Vehicle Routing Problem. The use of pheromones in the original ant colony algorithm was improved, and the waiting factor was added into the state transition rules to limit the information range. The improved ant colony algorithm was used to simulate the model with the example of aquatic product transportation route planning in Zhoushan city. The results show that this algorithm can optimize the transportation and distribution routes of aquatic products more effectively.