Robust Strategic Weight Manipulation Model with an Application to Environmental Assessment

被引:0
作者
Zuo, Lulu [1 ]
Ji, Ying [2 ]
Wang, Lun [1 ,2 ]
Wang, Zheng [1 ]
机构
[1] Univ Shanghai Sci & Technol, Business Sch, Shanghai 200093, Peoples R China
[2] Shanghai Univ, Sch Management, Shanghai 200444, Peoples R China
来源
POLISH JOURNAL OF ENVIRONMENTAL STUDIES | 2023年 / 32卷 / 02期
基金
中国国家自然科学基金;
关键词
robust optimization; strategic weight manipulation; uncertainty set; environmental assessment; DECISION-MAKING; NETWORK;
D O I
10.15244/pjoes/157490
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
In the increasingly complex and uncertain decision-making circumstances, interest groups and individuals will deliberately set attributes weight to manipulate the expected ranking of alternatives in order to achieve their benefits. However, it is not easy to change the ranking of alternatives, a certain compensation cost should be paid by decision makers. In previous studies, most scholars only considered the existence of unit compensation cost but ignored the uncertainty of compensation cost, which increased the risk of decision-making. In order to address the research gap, we construct two kinds of uncertainty sets in this work to describe the uncertainty of unit compensation cost more accurately. In addition, a robust strategic weight manipulation model is proposed with the presence of unit compensation cost uncertainty based on the robust optimization method to reduce the risk of the model. Furthermore, the proposed robust optimization model is applied to a numerical simulation of environmental assessment. The results show the applicability of the proposed method. Through comparison analysis and sensitivity analysis, we state that the proposed robust model is more scientific and effective than original model. Finally, some interesting conclusions and future research directions are given.
引用
收藏
页码:1957 / 1966
页数:10
相关论文
共 52 条
  • [1] Consensus-based robust decision making methods under a novel study of probabilistic uncertain linguistic information and their application in Forex investment
    Bashir, Zia
    Ali, Jawad
    Rashid, Tabasam
    [J]. ARTIFICIAL INTELLIGENCE REVIEW, 2021, 54 (03) : 2091 - 2132
  • [2] A stochastic dynamic programming approach to decision making in arranged marriages
    Batabyal, Amitrajeet A.
    Beladi, Hamid
    [J]. APPLIED MATHEMATICS LETTERS, 2011, 24 (12) : 2197 - 2200
  • [3] Robust convex optimization
    Ben-Tal, A
    Nemirovski, A
    [J]. MATHEMATICS OF OPERATIONS RESEARCH, 1998, 23 (04) : 769 - 805
  • [4] Robust solutions of uncertain linear programs
    Ben-Tal, A
    Nemirovski, A
    [J]. OPERATIONS RESEARCH LETTERS, 1999, 25 (01) : 1 - 13
  • [5] A relative robust approach on expected returns with bounded CVaR for portfolio selection
    Benati, S.
    Conde, E.
    [J]. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2022, 296 (01) : 332 - 352
  • [6] The price of robustness
    Bertsimas, D
    Sim, M
    [J]. OPERATIONS RESEARCH, 2004, 52 (01) : 35 - 53
  • [7] Robust discrete optimization and network flows
    Bertsimas, D
    Sim, M
    [J]. MATHEMATICAL PROGRAMMING, 2003, 98 (1-3) : 49 - 71
  • [8] Strategic weight manipulation in multiple attribute decision making
    Dong, Yucheng
    Liu, Yating
    Liang, Haiming
    Chiclana, Francisco
    Herrera-Viedma, Enrique
    [J]. OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE, 2018, 75 : 154 - 164
  • [9] Modeling uncertainty in multi-criteria decision analysis
    Durbach, Ian N.
    Stewart, Theodor J.
    [J]. EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2012, 223 (01) : 1 - 14
  • [10] Robust facility location in reverse logistics
    Egri, Peter
    David, Balazs
    Kis, Tamas
    Kresz, Miklos
    [J]. ANNALS OF OPERATIONS RESEARCH, 2023, 324 (1-2) : 163 - 188