Constraint Cellular Ant Algorithm for the Multi-Objective Vehicle Routing Problem

Abstract

Constraint Cellular ant algorithm is a new optimization method for solving real problems by using both constraints method, the evolutionary rule of cellular, graph theory and the characteristics of ant colony optimization. Multi-objective vehicle routing problem is very important and practical in logistic research fields, but it is difficult to model and solve because objectives have complicated relationship and restriction. Constraint Cellular ant algorithm has more obvious advantages to solve such kind of combinatorial optimization problems than many other algorithms. The test results show that the constraint cellular ant algorithm is feasible and effective for the MOVRP. The clarity and simplicity of the constraint cellular ant algorithm is greatly enhanced to ant colony optimization.