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Autor
Jardzioch Andrzej (West Pomeranian University of Technology Szczecin, Poland), Skobiej Bartosz (West Pomeranian University of Technology Szczecin, Poland)
Tytuł
Simulated Hardening Algorithm Application in Advanced Planning and Scheduling
Źródło
Przedsiębiorczość i Zarządzanie, 2016, t. 17, z. 12, cz. 2, s. 105-119, rys., tab., bibliogr. 13 poz.
Entrepreneurship and Management
Tytuł własny numeru
Systemy logistyczne w gospodarowaniu
Słowa kluczowe
Systemy workflow, Algorytmy, Zarządzanie przepływami pracy
Workflow systems, Algorithms, Workflow management
Uwagi
summ.
Abstrakt
This paper covers the problem of job scheduling for two-machine flow-shop system with unlimited transportation capability. The scope of the research complies with functionality of the decision support system (DSS) as a part of advanced planning and scheduling (APS). The 5 sets of random 500 jobs are introduced as the input sample. The simulated annealing (SA) algorithm with two variants of probability functions is used for delivering reference results. A new simulated hardening (SH) algorithm derived from SA is introduced and examined. Two optimization criteria are taken into consideration: makespan and profit. The results obtained with the two algorithms are compared and their usefulness in the problem presented is estimated. (original abstract)
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Bibliografia
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  1. Abdullah M., Othman M. (2014), Simulated annealing approach to cost-based multi-quality of service job scheduling in cloud computing enviroment, "American Journal of Applied Sciences", 11(6).
  2. Bessedik M., Benbouzid-Si Tayeb F., Cheurfi H., Blizak A. (2016), An immunity-based hybrid genetic algorithms for permutation flowshop scheduling problems, "International Journal of Advanced Manufacturing Technology", 85.
  3. Caliş B., Bulkan S. (2015), A research survey: review of AI solution strategies of job shop scheduling problem, "Journal of Intelligent Manufacturing", 26(5).
  4. Černy V. (1985), Thermodynamical approach to the traveling salesman problem: An efficient simulation algorithm, "Journal of Optimization Theory and Applications", Volume 45.
  5. Dzikuć M., Kuzdowicz P. (2006), ProALPHA APS - The Advanced tool for multi-resource-planning and realtime-optimization in middle-size enterprises, Zielona Góra, University of Zielona Góra.
  6. Gao C., Gao Y., Lv S. (2016), Improved simulated annealing algorithm for flexible job shop scheduling problems, Yinchuan, Institute of Electrical and Electronics Engineers Inc.
  7. Gao K. et al. (2016), An improved artificial bee colony algorithm for flexible job-shop scheduling problem with fuzzy processing time, "Expert Systems with Applications", 65.
  8. Khachaturyan A., Semenovskaya S., Vainshtein B. (1979), Statistical-Thermodynamic Approach to Determination of Structure Amplitude Phases, "Sov.Phys. Crystallography", 24(5).
  9. Khachaturyan A., Semenovskaya S., Vainshtein B. (1981), The Thermodynamic Approach to the Structure Analysis of Crystals, "Acta Crystallographica", Volume A37.
  10. Kia R. et al. (2012), Solving a group layout design model of a dynamic cellular manufacturing system with alternative process routings, lot splitting and flexible reconfiguration by simulated annealing, "Computers and Operations Research", 39(11).
  11. Petrović M., Vuković N., Mitić M., Milijković Z. (2016), Integration of process planning and scheduling using chaotic particle swarm optimization algorithm, "Expert Systems with Applications", 64,.
  12. Wang X., Xie X., Cheng T. (2013), A modified artificial bee colony algorithm for order acceptance in two-machine flow shops, "International Journal of Production Economics", 141(1).
  13. Woo K. (2014), A job shop scheduling game with GA-based evaluation, "Applied Mathematics and Information Sciences", 8(5).
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ISSN
1733-2486
Język
eng
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