Genetic algorithms approach to vehicle routing problem: A food distribution firm application

Customer satisfaction plays the leading role while companies are competing with the global market conditions. To satisfy their customers, companies have to serve in a fast and efficient way. Vehicle Routing Problem (VRP), which is the most important part of logistics concept, is one of the problems that companies come across. On the other hand, taking place widely in the literature, for the solution of Vehicle Routing Problem, heuristic and meta heuristic methods are used. Being complicated with the increasing number of customers, these methods give the best or the nearest results to the problems. Genetic Algorithms, inspired by evolution theory, is preferred because of being simple in application and not including complex mathematical formulas.The aim of this study is to determine the suitable route for the vehicle fleets which serve to the big markets and minimize the cost of the recommended route of a distributor company, which takes place in food sector in Trabzon. In the solution of the problem, genetic algorithms, a meta heuristic method, is used. The locations of customers, who are served by the company, are defined and the distances are calculated in digital environment. Subsequently, the weekly data are compared with the routes of the vehicle fleets that are suggested by newly developed genetic algorithm model. The present system is compared with the developed solution and the recommended model is ascertained to better the total weekly distance in the ratio of 14.5%.