Investigation on genetic representations for vehicle routing problem

In recent decades, various metaheuristics, such as genetic algorithms (GA), have been proposed to solve the vehicle routing problem (VRP), a well-known class of combinatorial optimization problems. It is generally known that the scheme for genetic representation of the solution albeit the chromosome coding structure, can play a crucial role in GA. Consequently, this may have a profound impact on the algorithm's performance significantly. We propose and study three forms of genetic representations used in a hybrid genetic algorithm for solving the VRP and analyze their influence on the performance of the algorithm. Algorithms with the different solution coding schemes were applied to a test case scenario of supply chain distribution network.