A hybrid genetic-simulated annealing algorithm for the location-inventory-routing problem considering returns under e-supply chain environment.
Facility location, inventory control, and vehicle routes scheduling are critical and highly related problems in the design of logistics system for e-business. Meanwhile, the return ratio in Internet sales was significantly higher than in the traditional business. Many of returned merchandise have no quality defects, which can reenter sales channels just after a simple repackaging process. Focusing on the existing problem in e-commerce logistics system, we formulate a location-inventory-routing problem model with no quality defects returns. To solve this NP-hard problem, an effective hybrid genetic simulated annealing algorithm (HGSAA) is proposed. Results of numerical examples show that HGSAA outperforms GA on computing time, optimal solution, and computing stability. The proposed model is very useful to help managers make the right decisions under e-supply chain environment.
School of Information Management, Central China Normal University, Wuhan 430079, China.
Yanhui
Y
Li
School of Information Management, Central China Normal University, Wuhan 430079, China.
Hao
H
Guo
School of Management, Huazhong University of Science and Technology, Wuhan 430074, China.
Lin
L
Wang
School of Information Management, Central China Normal University, Wuhan 430079, China ; Department of Industrial and System Engineering, State University of New York at Buffalo, Buffalo, NY 14228, USA.
Jing
J
Fu
D000465:Algorithms; D020407:Internet; D008962:Models, Theoretical