A multi-objective optimization of contamination algorithm for a contaminated region

被引:0
|
作者
Fedossova, Alina [1 ]
Fedosov, Valery [1 ]
机构
[1] Univ Nacl Colombia, Bogota, Colombia
关键词
contaminated region; emissions; pollution norms; semi-infinite optimization; decision making;
D O I
10.17981/ingecuc.20.1.2024.02
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Introduction: This work considers an industrial ecology problem under the framework of semi-infinite optimization. Objective: The objective is to resolve the conflict between pollutant emissions and environmental standards for the areas within a given region. Methodology: A version of the SIP2 algorithm is proposed, which simultaneously allows for a reduction in pollution while also enabling an increase in emissions from sources. This approach provides a certain degree of flexibility in managing pollution and the factors that cause it in the industry, while ensuring compliance with environmental regulations. Results: The results of two algorithms show different roles of the sources in obtaining the total pollution and, therefore, the need for changes in their emissions. Conclusions: The proposed algorithm offers more costeffective solutions in infrastructure design evaluations for areas with conflicting interests, such as maintenance or increasing production (indirectly measured by emissions generated from the production system), while ensuring compliance with restrictive environmental regulations.
引用
收藏
页码:1 / 10
页数:10
相关论文
共 50 条
  • [1] A new hybrid memetic multi-objective optimization algorithm for multi-objective optimization
    Luo, Jianping
    Yang, Yun
    Liu, Qiqi
    Li, Xia
    Chen, Minrong
    Gao, Kaizhou
    INFORMATION SCIENCES, 2018, 448 : 164 - 186
  • [2] Multi-objective boxing match algorithm for multi-objective optimization problems
    Tavakkoli-Moghaddam, Reza
    Akbari, Amir Hosein
    Tanhaeean, Mehrab
    Moghdani, Reza
    Gholian-Jouybari, Fatemeh
    Hajiaghaei-Keshteli, Mostafa
    EXPERT SYSTEMS WITH APPLICATIONS, 2024, 239
  • [3] Hyper multi-objective evolutionary algorithm for multi-objective optimization problems
    Guo, Weian
    Chen, Ming
    Wang, Lei
    Wu, Qidi
    SOFT COMPUTING, 2017, 21 (20) : 5883 - 5891
  • [4] MOCSA: A Multi-Objective Crow Search Algorithm for Multi-Objective Optimization
    Nobahari, Hadi
    Bighashdel, Ariyan
    2017 2ND CONFERENCE ON SWARM INTELLIGENCE AND EVOLUTIONARY COMPUTATION (CSIEC), 2017, : 60 - 65
  • [5] Multi-Objective A* Algorithm for the Multimodal Multi-Objective Path Planning Optimization
    Jin, Bo
    2021 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC 2021), 2021, : 1704 - 1711
  • [6] Modified Multi-Objective Particle Swarm Optimization Algorithm for Multi-objective Optimization Problems
    Qiao, Ying
    ADVANCES IN SWARM INTELLIGENCE, ICSI 2012, PT I, 2012, 7331 : 520 - 527
  • [7] Hyper multi-objective evolutionary algorithm for multi-objective optimization problems
    Weian Guo
    Ming Chen
    Lei Wang
    Qidi Wu
    Soft Computing, 2017, 21 : 5883 - 5891
  • [8] Hybrid Multi-Objective Genetic Algorithm for Multi-Objective Optimization Problems
    Zhang, Song
    Wang, Hongfeng
    Yang, Di
    Huang, Min
    2015 27TH CHINESE CONTROL AND DECISION CONFERENCE (CCDC), 2015, : 1970 - 1974
  • [9] A trust-region-like algorithm for expensive multi-objective optimization
    Liu, Hongwei
    Zhou, Changcong
    Liu, Fuchao
    Duan, Zunyi
    Zhao, Haodong
    APPLIED SOFT COMPUTING, 2023, 148
  • [10] A Decentralized Multi-objective Optimization Algorithm
    Blondin, Maude J.
    Hale, Matthew
    JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS, 2021, 189 (02) : 458 - 485