Optimizing Multi-depot Vehicle Routing: An Abc-ga Hybrid Algorithm

Abstract The multi-depot vehicle routing problem (MDVRP) is a generalized form of the vehicle routing problem (VRP) and travelling salesman problem (TSP). It is considered as one of the NP-hard problems. The Multi-Depot Vehicle Routing Problem (MDVRP) is a logistics problem that involves finding the most efficient route to transport goods between multiple different pickup and delivery locations. In this study a hybrid metaheuristic algorithm that integrates Artificial Bee colony and genetic algorithms is developed to solve a Multi-Depot Vehicle routing problem (MDVRP). The main objective of this study is to find the optimal route from multiple depots to serve a set of customers dispersed in different geographical location. Initially nearest neighborhood algorithm is used to assign customer to their nearest depot and randomly generated initial solution. Then the solutions are modified applying ABCGA hybrid algorithm. ABC algorithm is the main algorithm where genetic algorithm is used inside the employee be phase and onlooker bee phase. Then one of the operators applied from ABC neighborhood search, GA, 2 opt local search based on the probabilistic selection.