Name
Title | ||
|---|---|---|
An Improved Differential Evolution Algorithm for a Multicommodity Location-Inventory Problem with False Failure Returns. |
Abstract | ||
|---|---|---|
Customer returns are a common phenomenon in many industries, and they have a significant impact on business organizations and their supply chains. False failure returns are returned products that have no functional or cosmetic defects, and they represent a large body of customer returns in practice. In this paper, we develop a mixed-integer nonlinear programming model to study a multicommodity location-inventory problem in a forward-reverse logistics network. This model minimizes the total cost in this network by considering false failure returns, and it also considers many real-world business scenarios in forward and reverse logistics flows. Moreover, we design a new heuristic approach to solve the model efficiently. Finally, numerical experiments are conducted to validate our solution approach and provide meaningful managerial insights. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1155/2018/1967398 | COMPLEXITY |
Field | DocType | Volume |
Mathematical optimization,Heuristic,Reverse logistics,Nonlinear programming,Artificial intelligence,Supply chain,Total cost,Differential evolution algorithm,Machine learning,Mathematics | Journal | 2018 |
ISSN | Citations | PageRank |
1076-2787 | 0 | 0.34 |
References | Authors | |
17 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Cong-Dong Li | 1 | 8 | 3.20 |
| Hao Guo | 2 | 2 | 0.71 |
| Ying Zhang | 3 | 42 | 2.69 |
| Shuai Deng | 4 | 0 | 0.34 |
| Yu Wang | 5 | 4 | 1.77 |