Optimization of VRR for Cold Chain with Minimum Loss Based on Actual Traffic Conditions

Recently, fresh agricultural cold-chain logistics have been greatly developed with the increasing needs of people's life. Reducing costs of cold-chain distribution has become the main object of loss control in logistics enterprises. The objective of this research is to find a set of optimal routes that minimize the total loss, including fuel cost, refrigeration cost, soft time window penalty cost, and cargo damage cost over transit time. In this paper, the definition and model construction of vehicle routing problem (VRP) with multiobjective minimum lost are introduced first. Then, an ant colony optimization (ACO) algorithm combined with Pareto local search (PLS) is put forward to solve the minimum loss model. In order to avoid the influence of complex road conditions during distribution, the distance matrix and the transit time matrix are both derived from the recommended navigation road based on E-map API. At last, a compare experiment between the traditional method and our proposed method is performed. The results indicate that our method has strong applicability and potential advantages in cold-chain logistic and has important practical significance and application value.

Automated summary

The study aims to find optimal routes to minimize total losses in cold-chain logistics, using an ant colony optimization algorithm combined with Pareto local search for solving. The experiment results show that the method has strong applicability and potential advantages, with important practical significance and application value.