On Multiobjective Knapsack Problems with Multiple Decision Makers

Zhen Song; Wenjian Luo; Xin Lin; Zeneng She; Qingfu Zhang

doi:10.1109/SSCI51031.2022.10022188

On Multiobjective Knapsack Problems with Multiple Decision Makers

Zhen Song
, Wenjian Luo^*
, Xin Lin
, Zeneng She
, Qingfu Zhang

^*Corresponding author for this work

Department of Computer Science

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

9 Citations (Scopus)

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.

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
DOIs	https://doi.org/10.1109/SSCI51031.2022.10022188
Publication status	Published - Dec 2022
Event	2022 IEEE Symposium Series on Computational Intelligence (SSCI 2022) - Singapore Management University, Singapore Duration: 4 Dec 2022 → 7 Dec 2022 https://ieeexplore.ieee.org/xpl/conhome/10022049/proceeding

Publication series

Name	Proceedings of the IEEE Symposium Series on Computational Intelligence, SSCI

Conference

Conference	2022 IEEE Symposium Series on Computational Intelligence (SSCI 2022)
Place	Singapore
Period	4/12/22 → 7/12/22
Internet address	https://ieeexplore.ieee.org/xpl/conhome/10022049/proceeding

Research Keywords

evolutionary computation
knapsack problem
Multiobjective optimization
multiparty multiobjective optimization

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10.1109/SSCI51031.2022.10022188

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Song, Z., Luo, W., Lin, X., She, Z., & Zhang, Q. (2022). On Multiobjective Knapsack Problems with Multiple Decision Makers. In H. Ishibuchi, C.-K. Kwoh, A.-H. Tan, D. Srinivasan, C. Miao, A. Trivedi, & K. Crockett (Eds.), Proceedings of the 2022 IEEE Symposium Series on Computational Intelligence (SSCI 2022) (pp. 156-163). (Proceedings of the IEEE Symposium Series on Computational Intelligence, SSCI ). IEEE. https://doi.org/10.1109/SSCI51031.2022.10022188

Song, Zhen ; Luo, Wenjian ; Lin, Xin et al. / On Multiobjective Knapsack Problems with Multiple Decision Makers. Proceedings of the 2022 IEEE Symposium Series on Computational Intelligence (SSCI 2022). editor / Hisao Ishibuchi ; Chee-Keong Kwoh ; Ah-Hwee Tan ; Dipti Srinivasan ; Chunyan Miao ; Anupam Trivedi ; Keeley Crockett. IEEE, 2022. pp. 156-163 (Proceedings of the IEEE Symposium Series on Computational Intelligence, SSCI ).

@inproceedings{edd44fbec71f486dac9b68f2ba7f02af,

title = "On Multiobjective Knapsack Problems with Multiple Decision Makers",

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. {\textcopyright} 2022 IEEE.",

keywords = "evolutionary computation, knapsack problem, Multiobjective optimization, multiparty multiobjective optimization",

author = "Zhen Song and Wenjian Luo and Xin Lin and Zeneng She and Qingfu Zhang",

year = "2022",

month = dec,

doi = "10.1109/SSCI51031.2022.10022188",

language = "English",

isbn = "978-1-6654-8769-6",

series = "Proceedings of the IEEE Symposium Series on Computational Intelligence, SSCI ",

publisher = "IEEE",

pages = "156--163",

editor = "Hisao Ishibuchi and Chee-Keong Kwoh and Tan, \{Ah-Hwee \} and Dipti Srinivasan and Chunyan Miao and Anupam Trivedi and Keeley Crockett",

booktitle = "Proceedings of the 2022 IEEE Symposium Series on Computational Intelligence (SSCI 2022)",

address = "United States",

note = "2022 IEEE Symposium Series on Computational Intelligence (SSCI 2022) ; Conference date: 04-12-2022 Through 07-12-2022",

url = "https://ieeexplore.ieee.org/xpl/conhome/10022049/proceeding",

}

Song, Z, Luo, W, Lin, X, She, Z & Zhang, Q 2022, On Multiobjective Knapsack Problems with Multiple Decision Makers. in H Ishibuchi, C-K Kwoh, A-H Tan, D Srinivasan, C Miao, A Trivedi & K Crockett (eds), Proceedings of the 2022 IEEE Symposium Series on Computational Intelligence (SSCI 2022). Proceedings of the IEEE Symposium Series on Computational Intelligence, SSCI , IEEE, pp. 156-163, 2022 IEEE Symposium Series on Computational Intelligence (SSCI 2022), Singapore, 4/12/22. https://doi.org/10.1109/SSCI51031.2022.10022188

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 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - On Multiobjective Knapsack Problems with Multiple Decision Makers

AU - Song, Zhen

AU - Luo, Wenjian

AU - Lin, Xin

AU - She, Zeneng

AU - Zhang, Qingfu

PY - 2022/12

Y1 - 2022/12

N2 - 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.

AB - 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.

KW - evolutionary computation

KW - knapsack problem

KW - Multiobjective optimization

KW - multiparty multiobjective optimization

UR - https://www.scopus.com/pages/publications/85147795009

UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85147795009&origin=recordpage

U2 - 10.1109/SSCI51031.2022.10022188

DO - 10.1109/SSCI51031.2022.10022188

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 978-1-6654-8769-6

T3 - Proceedings of the IEEE Symposium Series on Computational Intelligence, SSCI

SP - 156

EP - 163

BT - Proceedings of the 2022 IEEE Symposium Series on Computational Intelligence (SSCI 2022)

A2 - Ishibuchi, Hisao

A2 - Kwoh, Chee-Keong

A2 - Tan, Ah-Hwee

A2 - Srinivasan, Dipti

A2 - Miao, Chunyan

A2 - Trivedi, Anupam

A2 - Crockett, Keeley

PB - IEEE

T2 - 2022 IEEE Symposium Series on Computational Intelligence (SSCI 2022)

Y2 - 4 December 2022 through 7 December 2022

ER -

Song Z, Luo W, Lin X, She Z, Zhang Q. On Multiobjective Knapsack Problems with Multiple Decision Makers. In Ishibuchi H, Kwoh CK, Tan AH, Srinivasan D, Miao C, Trivedi A, Crockett K, editors, Proceedings of the 2022 IEEE Symposium Series on Computational Intelligence (SSCI 2022). IEEE. 2022. p. 156-163. (Proceedings of the IEEE Symposium Series on Computational Intelligence, SSCI ). doi: 10.1109/SSCI51031.2022.10022188

On Multiobjective Knapsack Problems with Multiple Decision Makers

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