Optimization of a multi-objective-multi period traveling salesman problem with pickup and delivery using genetic algorithm

Abstract

Nowadays, managerial decisions regarding how to select the company’s strategy between a responsive or cost effective manner to serve the customers, contributes a lot to a firm's competitiveness. It takes many factors into consideration one of which is the sequence of customers to be visited in a logistics system. The Travelling Salesman Problem (TSP) is one of the most famous combinatorial optimization problems in this area. Optimization of such problem would directly affect the total cost and also customer satisfaction level in that system. This study aims at proposing a new extension of TSP which is ‘multi-objective-multi-period Travelling Salesman Problem with pickup and delivery’ to represent the problem. The cost studied in this research is transportation cost associated with travel time. Delivery time (the secondary objective in the objective function) is considered as the only influential factor on the customer satisfaction. Optimization of the proposed model is done using Genetic Algorithm. The proposed model has been tested on data collected from a Company from service sector. The applied algorithm has been encoded by Matlab software. Final results are given illustrating the validity and practicality of the proposed model for different strategies in a company according to its customer’s expectation.