Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4959136 | Computers & Operations Research | 2017 | 27 Pages |
Abstract
The multi-product dynamic lot sizing problem with product returns and recovery is an important problem that appears in reverse logistics and is known to be NP-hard. In this paper we propose an efficient variable neighborhood descent heuristic algorithm for solving this problem. Furthermore, we present a new benchmark set with the largest instances in the literature. The computational results demonstrate that our approach outperforms the state-of-the-art Gurobi optimizer.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science (General)
Authors
Angelo Sifaleras, Ioannis Konstantaras,