Industrial cost modelling and multi-objective optimisation for decision support in production systems development

被引:22
|
作者
Pehrsson, Leif [1 ]
Ng, Amos H. C. [1 ]
Stockton, David [2 ]
机构
[1] Univ Skovde, Virtual Syst Res Ctr, SE-54128 Skovde, Sweden
[2] De Montfort Univ, Ctr Mfg, Leicester LE1 9BH, Leics, England
关键词
Cost model; Simulation; Optimisation; Decision support; Manufacturing; Production system;
D O I
10.1016/j.cie.2013.08.011
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Recent developments in cost modelling, simulation-based multi-objective optimisation, and post-optimality analysis have enabled the integration of costing data and cost estimation into a new methodology for supporting economically sound decision-making in manufacturing enterprises. Within this methodology, the combination of production engineering and financial data with multi-objective optimisation and post-optimality analysis has been proven to provide the essential information to facilitate knowledge-driven decision-making in real-world production systems development. The focus of this paper is to present the incremental cost modelling technique specifically designed for the integration with discrete-event simulation models and multi-objective optimisation within this methodology. A complete example, using the simulation model and data modified from a previous real-world case study, is provided in this paper to illustrate how the methodology and cost modelling are applied for the optimal investment decision support. (C) 2013 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1036 / 1048
页数:13
相关论文
共 50 条
  • [1] Integration of data mining and multi-objective optimisation for decision support in production systems development
    Dudas, Catarina
    Ng, Amos H. C.
    Pehrsson, Leif
    Bostrom, Henrik
    [J]. INTERNATIONAL JOURNAL OF COMPUTER INTEGRATED MANUFACTURING, 2014, 27 (09) : 824 - 839
  • [2] Reproducible decision support for industrial decision making using a knowledge extraction platform on multi-objective optimisation data
    Lidberg, Simon
    Ng, Amos H. C.
    [J]. INTERNATIONAL JOURNAL OF MANUFACTURING RESEARCH, 2023, 18 (04) : 454 - 480
  • [3] The development of a fuzzy multi-objective group decision support system
    Wu, Fengjie
    Lu, He
    Zhang, Guangquan
    Ruan, Da
    [J]. 2007 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS, VOLS 1-4, 2007, : 669 - +
  • [4] Solar assisted heat engine systems: multi-objective optimisation and decision making
    Rao, R. Venkata
    Keesari, Hameer Singh
    [J]. INTERNATIONAL JOURNAL OF AMBIENT ENERGY, 2019, : 149 - 175
  • [5] Solar assisted heat engine systems: multi-objective optimisation and decision making
    Rao, R. Venkata
    Keesari, Hameer Singh
    [J]. International Journal of Ambient Energy, 2022, 43 (01) : 149 - 175
  • [6] Multi-Objective Optimisation of Container Orchestration Systems
    Reitzl, Marcus
    Kimovski, Dragi
    [J]. 16TH IEEE/ACM INTERNATIONAL CONFERENCE ON UTILITY AND CLOUD COMPUTING, UCC 2023, 2023,
  • [7] Decision/Objective Space Trajectory Networks for Multi-objective Combinatorial Optimisation
    Ochoa, Gabriela
    Liefooghe, Arnaud
    Lavinas, Yuri
    Aranha, Claus
    [J]. EVOLUTIONARY COMPUTATION IN COMBINATORIAL OPTIMIZATION, EVOCOP 2023, 2023, 13987 : 211 - 226
  • [8] Review of cost objective functions in multi-objective optimisation analysis of buildings
    Auza, Anna
    Asadi, Ehsan
    Chenari, Behrang
    da Silva, Manuel Gameiro
    [J]. RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2024, 191
  • [9] Multi-Objective Decision Support for Irrigation Systems Based on Skyline Query
    Loh, Chee-Hoe
    Chen, Yi-Chung
    Su, Chwen-Tzeng
    Lin, Sheng-Hao
    [J]. APPLIED SCIENCES-BASEL, 2024, 14 (03):
  • [10] Multi-objective optimisation
    Bortfeld, T.
    [J]. RADIOTHERAPY AND ONCOLOGY, 2007, 84 : S72 - S73