Developing an evolutionary algorithm for the Vehicle Routing Problem in Large Scale Network

This paper presents an application of a novel nature-inspired algorithm to the basic Vehicle Routing Problem (VRP) in a large scale network, which customers of known demand are supplied from a single depot. Vehicles are subject to a weight limit, and in some cases, to a limit on the distance travelled. Only one vehicle is allowed to supply each customer. In order to address the proposed problem, a new meta-heuristics inspired by Red Deer’s mating is presented (RDA). This issue aims to explore the RDA on the proposed VRP for the first time. To check the performance of meta-heuristic, an exact solution solver, Branch and Bound (B&B), is utilized by LINGO software. Further results are given using an Imperialist Competitive Algorithm (ICA) and Genetic Algorithm (GA), showing that RDA is competitive with other strong meta-heuristics in terms of solution time and quality of results.

Keywords:

Vehicle Routing Problem (VRP) , Meta-heuristics , Red Deer Algorithm (RDA)