A bi-objective model in sustainable dynamic cell formation problem with skill-based worker assignment

被引:62
|
作者
Niakan, Farzad [1 ]
Baboli, Armand [1 ]
Moyaux, Thierry [1 ]
Botta-Genoulaz, Valerie [1 ]
机构
[1] Univ Lyon, INSA Lyon, DISP Lab, EA4570, Villeurbanne, France
关键词
Dynamic cell formation; Sustainability; Bi-objective optimization; Non-dominated Sorting Genetic Algorithm; Multi-Objective Simulated Annealing; LAYOUT DESIGN-MODEL; MATHEMATICAL-MODEL; GENETIC-ALGORITHM; MANUFACTURING SYSTEM;
D O I
10.1016/j.jmsy.2015.11.001
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The most recent revolution in industry (Industrial Revolution 4.0) requires increased flexibility, agility and efficiency in the use of production equipment. The Dynamic Cellular Manufacturing System (DCMS) is one of the best production systems to meet such requirements. In addition, the increasing importance of environmental and social issues, along with recent laws, is forcing manufacturers and managers to take account of sustainability when designing and configuring manufacturing systems. This paper proposes a new bi-objective mathematical model of the Dynamic Cell Formation Problem (DCFP), in which the worker's assignment, environmental and social criteria are considered. The first objective in this model is to minimize both production and labor costs while the total production waste (e.g., energy, chemical material, raw material, CO2 emissions, etc.) is minimized as second objective. Social criteria in this model, are represented as constraint. Due to the NP-hardness of this problem, we propose a new resolution approach called NSGA II-MOSA, that merges an efficient hybrid meta-heuristic based on the Non-dominated Sorting Genetic Algorithm (NSGA-II), with Multi-Objective Simulated Annealing (MOSA). Finally, randomly-generated test problems demonstrate the performance of our algorithm. (C) 2015 The Society of Manufacturing Engineers. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:46 / 62
页数:17
相关论文
共 50 条
  • [41] Emergency evacuation paths for tank farm fires based on bi-objective dynamic planning
    Chou, Guanbo
    Duo, Yili
    Liu, Jie
    Sun, Lin
    Zhang, Yuyuan
    Sun, Tie
    SCIENTIFIC REPORTS, 2025, 15 (01):
  • [42] Decomposition-based bi-objective optimization for sustainable robotic assembly line balancing problems
    Zhou, Binghai
    Wu, Qiong
    JOURNAL OF MANUFACTURING SYSTEMS, 2020, 55 : 30 - 43
  • [43] A bi-objective mathematical model to determine risk-based inspection programs
    Javid, Y.
    PROCESS SAFETY AND ENVIRONMENTAL PROTECTION, 2021, 146 : 893 - 904
  • [44] Bi-objective optimization-based multi-criteria decision-making framework for disassembly line balancing and employee assignment problem
    Deniz, Nurcan
    Ozcelik, Feristah
    KYBERNETES, 2024, 53 (03) : 1073 - 1091
  • [45] Disinformation spreading control model based on key nodes bi-objective optimization
    Jing J.
    Zhang Z.
    Ban A.
    Gao D.
    Xi'an Dianzi Keji Daxue Xuebao/Journal of Xidian University, 2024, 51 (01): : 201 - 209
  • [47] A bi-objective fleet size and mix green inventory routing problem, model and solution method
    Alinaghian, Mehdi
    Zamani, Mohsen
    SOFT COMPUTING, 2019, 23 (04) : 1375 - 1391
  • [48] Sustainable hierarchical multi-modal hub network design problem: bi-objective formulations and solution algorithms
    Mohammad Mahdi Nasiri
    Amir Khaleghi
    Kannan Govindan
    Ali Bozorgi-Amiri
    Operational Research, 2023, 23
  • [49] Sustainable hierarchical multi-modal hub network design problem: bi-objective formulations and solution algorithms
    Nasiri, Mohammad Mahdi
    Khaleghi, Amir
    Govindan, Kannan
    Bozorgi-Amiri, Ali
    OPERATIONAL RESEARCH, 2023, 23 (02)
  • [50] A Path Relinking-Based Approach for the Bi-Objective Double Floor Corridor Allocation Problem
    Uribe, Nicolas R.
    Herran, Alberto
    Manuel Colmenar, J.
    ADVANCES IN ARTIFICIAL INTELLIGENCE, CAEPIA 2024, 2024, : 111 - 120