An advanced hybrid meta-heuristic algorithm for the vehicle routing problem with backhauls and time windows

Date

2015-08

Authors

Journal Title

Journal ISSN

Volume Title

Publisher

Pergamon Elsevier Science

Abstract

This paper presents an advanced hybrid meta-heuristic algorithm (HMA) to solve the vehicle routing problem with backhauls and time windows (VRPBTW). The VRPBTW is an extension of the vehicle routing problem with time windows (VRPTW) and the vehicle routing problem with backhauls (VRPB) that includes capacity, backhaul and time window constraints. In this problem, the customers are divided into two subsets consisting of linehaul and backhaul customers. Each vehicle starts from the depot, and goods are delivered from the depot to the linehaul customers. Goods are subsequently returned to the depot from the backhaul customers. The objective is to minimize the total distance that satisfies all of the constraints. The proposed meta-heuristic method is tested on a problem data set obtained from Solomon's VRPTW benchmark problems which includes 25, 50 and 100 demand nodes. The results of the computational studies show that the HMA outperforms the existing studies and provides better solutions than the best known solutions in practical computational times.

Description

Keywords

Computer science, Engineering, Vehicle routing problem, Hybrid meta-heuristic algorithm, Simulated annealing, Tabu search, Scheduling Problems, Optimization, Delivery, Pickup, Algorithms, Heuristic algorithms, Hybrid vehicles, Network routing, Routing algorithms, Sales, Simulated annealing, Heuristic methods, Vehicle routing, Vehicles, Bench-mark problems, Computational studies, Computational time, Hybrid meta-heuristic, Meta-heuristic methods, Time window constraint, Vehicle routing problem with time windows, Vehicle routing problems

Citation

Küçükoğlu, İ. ve Öztürk, N. (2015). "An advanced hybrid meta-heuristic algorithm for the vehicle routing problem with backhauls and time windows". Computers and Industrial Engineering, 86, 60-68.