Bu öğeden alıntı yapmak, öğeye bağlanmak için bu tanımlayıcıyı kullanınız:
http://hdl.handle.net/11452/28602
Başlık: | An advanced hybrid meta-heuristic algorithm for the vehicle routing problem with backhauls and time windows |
Yazarlar: | Uludağ Üniversitesi/Mühendislik Fakültesi/Endüstri Mühendisliği Bölümü. 0000-0002-5075-0876 Küçükoğlu, İlker Öztürk, Nursel D-8543-2015 AAG-9336-2021 55763879600 7005688805 |
Anahtar kelimeler: | 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 |
Yayın Tarihi: | Ağu-2015 |
Yayıncı: | Pergamon Elsevier Science |
Atıf: | 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. |
Özet: | 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 |
Koleksiyonlarda Görünür: | Scopus Web of Science |
Bu öğenin dosyaları:
Bu öğeyle ilişkili dosya bulunmamaktadır.
DSpace'deki bütün öğeler, aksi belirtilmedikçe, tüm hakları saklı tutulmak şartıyla telif hakkı ile korunmaktadır.