| Title |
A Generalized Circular Supply Chain Problem for Multi-objective Evolutionary Algorithms |
| ID_Doc |
24802 |
| Authors |
Benecke, T; Antons, O; Mostaghim, S; Arlinghaus, J |
| Title |
A Generalized Circular Supply Chain Problem for Multi-objective Evolutionary Algorithms |
| Year |
2023 |
| Published |
|
| DOI |
10.1145/3583133.3590742 |
| Abstract |
The idea of a circular economy proves promising with the ever-growing need for more sustainable production methods and resource utilization. However, this introduces new challenges compared to the traditional, mostly linear production processes and often leads to a tradeoff between sustainability and costs. In these environments, multi-objective evolutionary algorithms (MOEAs) are a great tool to tackle the increased complexity of supply chains in a circular economy. While MOEAs have been used to optimize circular supply chain models in the past, it was usually done for specific industries and using standard operators. In this paper, we propose a generalized test problem to provide a tool for evaluating MOEAs with respect to a circular supply chain (CSC) problem. In this problem, we try to optimize the product plan as well as the material sourcing at the same time, considering the objectives of maximizing the profit and sustainable resource use. |
| Author Keywords |
multi-objective optimization; supply chain optimization; evolutionary algorithms; benchmarking |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Conference Proceedings Citation Index - Science (CPCI-S) |
| EID |
WOS:001117972600111 |
| WoS Category |
Computer Science, Artificial Intelligence; Computer Science, Information Systems |
| Research Area |
Computer Science |
| PDF |
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