Development and Comparison of Four GA based Algorithms for Heterogeneous Vehicle Routing Problem with Time Windows

Heterogeneous Vehicle Routing Problem with Time Windows is the most practical variant of Vehicle Routing Problem due to its complexity. It belongs to the NP-Hard combinatorial problem. Because of its applications, it has become a popular choice among researchers and practitioners. In the first part of this research, a brief introduction of supply chain management has been provided. Then, an extensive literature review on various meta-heuristics for solving the Heterogeneous Vehicle Routing Problem and its variants has been presented. Based on the brief literature review, the Heterogeneous Vehicle Routing Problem with Time Windows is selected as the research problem. Since Heterogeneous Vehicle Routing Problem with Time Windows is combinatorial and NP-Hard in nature, in this research, four metaheuristics based on Genetic Algorithm are developed for solving it. The proposed four algorithms are compared using a Complete Factorial Experiment with three factors, viz. GA Method, Problem Size and Mutation Probability. Since the factor “GA Method” is significant, the best algorithm has been identified by using Duncan's Multiple Range Test.