On Multiobjective Knapsack Problems with Multiple Decision Makers
Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45) › 32_Refereed conference paper (with ISBN/ISSN) › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 2022 IEEE Symposium Series on Computational Intelligence (SSCI 2022) |
| Editors | Hisao Ishibuchi, Chee-Keong Kwoh, Ah-Hwee Tan, Dipti Srinivasan, Chunyan Miao, Anupam Trivedi, Keeley Crockett |
| Publisher | IEEE |
| Pages | 156-163 |
| ISBN (Electronic) | 9781665487689 |
| ISBN (Print) | 978-1-6654-8769-6 |
| Publication status | Published - Dec 2022 |
Publication series
| Name | Proceedings of the IEEE Symposium Series on Computational Intelligence, SSCI |
|---|
Conference
| Title | 2022 IEEE Symposium Series on Computational Intelligence (SSCI 2022) |
|---|---|
| Location | Singapore Management University |
| Place | Singapore |
| Period | 4 - 7 December 2022 |
Link(s)
Abstract
Many real-world optimization problems require optimizing multiple conflicting objectives simultaneously, and such problems are called multiobjective optimization problems (MOPs). As a variant of the classical knapsack problems, multi-objective knapsack problems (MOKPs), exist widely in the real-world applications, e.g., cargo loading, project and investment selection. There is a special class of MOKPs called multiparty multiobjective knapsack problems (MPMOKPs), which involve multiple decision makers (DMs) and each DM only cares about some of all the objectives. To the best of our knowledge, little work has been conducted to address MPMOKPs. In this paper, a set of benchmarks which have common Pareto optimal solutions for MPMOKPs is proposed. Besides, we design a SPEA2-based algorithm, called SPEA2-MP to solve MPMOKPs, which aims at finding the common Pareto optimal solutions to satisfy multiple decision makers as far as possible. Experimental results on the benchmarks have demonstrated the effectiveness of the proposed algorithm. © 2022 IEEE.
Research Area(s)
- evolutionary computation, knapsack problem, Multiobjective optimization, multiparty multiobjective optimization
Citation Format(s)
On Multiobjective Knapsack Problems with Multiple Decision Makers. / Song, Zhen; Luo, Wenjian; Lin, Xin et al.
Proceedings of the 2022 IEEE Symposium Series on Computational Intelligence (SSCI 2022). ed. / Hisao Ishibuchi; Chee-Keong Kwoh; Ah-Hwee Tan; Dipti Srinivasan; Chunyan Miao; Anupam Trivedi; Keeley Crockett. IEEE, 2022. p. 156-163 (Proceedings of the IEEE Symposium Series on Computational Intelligence, SSCI ).Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45) › 32_Refereed conference paper (with ISBN/ISSN) › peer-review
