A Meta-heuristic Approach to CVRP Problem: Local Search Optimization Based on GA and Ant Colony

The Capacitated Vehicle Routing Problem (CVRP) is well-known combintorialoptimization problem that holds a central place in logistics management. The VehicleRouting is an applied task in the industrial transportation for which an optimal solutionwill lead us to better services, save more time and ultimately increase in customersatisfaction. This problem is classified into NP-Hard problems and deterministicapproaches will be time- consuming to solve it. In this paper, we focus on enhancing thecapability of local search algorithms. We use six different meta-heuristic algorithms tosolve VRP considering the limited carrying capacity and we analyze their preformanceon the standard datasets. Finally, we propose an improved genetic algorithm and use theant colony algorithm to create the initial population. The experimental results show thatusing of heuristic local search algorithms to solve CVRP is suitable. The results arepromising and we observe the proposed algorithm has the best performance among itscounterparts.

Keywords:

Vehicle Routing Problem , Capacitated Vehicle Routing Problem , Meta-Heuristic Algorithms , Local Search , Genetic Algorithm