A multi-objective approach to the application of real-world production scheduling

被引:14
作者
Korosec, Peter [1 ]
Bole, Uros [2 ]
Papa, Gregor [1 ,2 ]
机构
[1] Jozef Stefan Inst, Comp Syst Dept, Ljubljana, Slovenia
[2] Jozef Stefan Int Postgrad Sch, Ljubljana, Slovenia
关键词
Combinatorial optimization; Decision support systems; Flexibility; Job shop scheduling; Multicriteria; MEMETIC ALGORITHMS; LOCAL SEARCH; DECISION-SUPPORT; JOB SHOPS; OPTIMIZATION; PARETO; TIME;
D O I
10.1016/j.eswa.2013.05.035
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
An initiative was introduced in one of the production facilities of Germany's E.G.O. Group in order to enhance its SAP information system with a custom-made application for production-scheduling optimization. The goal of the optimization is to find a production schedule that satisfies different, contradictory production and business constraints. We show the challenges faced in the application of the multi-objective optimization approach, which is gaining influence in the management of production scheduling. We implement a memetic version of the Indicator-Based Evolutionary Algorithm with customized reproduction operators and local search procedures to find a set of feasible, non-dominated solutions. Such a memetic algorithm was applied to two real order lists from the production company. Additionally, we also lay out an efficient presentation of the multi-objective results for an expert's support in decision making. This provides the management with the possibility to gain additional insights into how the production schedule dynamically reacts to changes in the decision criteria. We show that the multi-objective approach is able to find high-quality solutions, which enables flexibility when it comes to quickly adapting to specific business conditions. (C) 2013 Elsevier Ltd. All rights reserved.
引用
收藏
页码:5839 / 5853
页数:15
相关论文
共 39 条
  • [21] Jing Gong, 2010, 2010 2nd International Conference on Mechanical and Electrical Technology (ICMET), P384, DOI 10.1109/ICMET.2010.5598388
  • [22] Knowles J, 2005, STUD FUZZ SOFT COMP, V166, P313
  • [23] The falling tide algorithm: A new multi-objective approach for complex workforce scheduling
    Li, Jingpeng
    Burke, Edmund K.
    Curtois, Tim
    Petrovic, Sanja
    Qu, Rong
    [J]. OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE, 2012, 40 (03): : 283 - 293
  • [24] Decision support for build-to-order supply chain management through multiobjective optimization
    Mansouri, S. Afshin
    Gallear, David
    Askariazad, Mohammad H.
    [J]. INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS, 2012, 135 (01) : 24 - 36
  • [25] Markus ML, 2002, MIS QUART, V26, P179
  • [26] A SUCCESSIVE APPROACH TO COMPUTE THE BOUNDED PARETO FRONT OF PRACTICAL MULTIOBJECTIVE OPTIMIZATION PROBLEMS
    Mueller-Gritschneder, Daniel
    Graeb, Helmut
    Schlichtmann, Ulf
    [J]. SIAM JOURNAL ON OPTIMIZATION, 2009, 20 (02) : 915 - 934
  • [27] Nareyek A., 2000, LECT NOTES COMPUTER, V2148
  • [28] Papa G., 2008, P GEN EV COMP C GECC, P1133
  • [29] Guided restarting local search for production planning
    Papa, Gregor
    Vukasinovic, Vida
    Korosec, Peter
    [J]. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2012, 25 (02) : 242 - 253
  • [30] A theory of lexicographic multi-criteria optimization
    Rentmeesters, MJ
    Tsai, WK
    Lin, KJ
    [J]. SECOND IEEE INTERNATIONAL CONFERENCE ON ENGINEERING OF COMPLEX COMPUTER SYSTEMS: HELD JOINTLY WITH 6TH CSESAW, 4TH IEEE RTAW, AND SES'96, 1996, : 76 - 79