A metaheuristic strategy for solving capacitated vehicle routing problem by using chaotic dynamics

The capacitated vehicle routing problem (CVRP) is one of the NP-hard combinatorial optimization problems, and efficient construction of a high-quality solution is a major challenge. In this paper, we propose a metaheuristic method based on chaotic dynamics to improve the efficiency of two local search operations: the CROSS-Exchange and the 2-opt methods. Unlike traditional methods that usually rely on randomization or fixed rules, this method dynamically controls the selection and execution of local search operations using chaotic neurodynamics. The experimental results show that this method can effectively improve the quality of the solution and algorithm performance when solving CVRP, and also provides a new solution framework for logistics optimization.