Please use this identifier to cite or link to this item: http://hdl.handle.net/11452/28602
Title: An advanced hybrid meta-heuristic algorithm for the vehicle routing problem with backhauls and time windows
Authors: Uludağ Üniversitesi/Mühendislik Fakültesi/Endüstri Mühendisliği Bölümü.
0000-0002-5075-0876
Küçükoğlu, İlker
Öztürk, Nursel
D-8543-2015
AAG-9336-2021
55763879600
7005688805
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
Issue Date: Aug-2015
Publisher: Pergamon Elsevier Science
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.
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.
URI: https://doi.org/10.1016/j.cie.2014.10.014
https://www.sciencedirect.com/science/article/pii/S0360835214003453
http://hdl.handle.net/11452/28602
ISSN: 0360-8352
1879-0550
Appears in Collections:Scopus
Web of Science

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