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Rationalization of Production Order Execution with Use of the Greedy and Tabu Search Algorithms

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International Joint Conference SOCO’18-CISIS’18-ICEUTE’18 (SOCO’18-CISIS’18-ICEUTE’18 2018)

Abstract

In the paper, rationalization of production order execution in a large manufacturing company is suggested. Till now, the decision-making process was based on the human factor, which resulted in irregular utilization of manufacturing resources. The presented work was aimed at developing new order selection system. That would make it possible to utilize the admitted resources possibly best and thus to meet the deadlines and to adapt to specific production requirements. In the work, the greedy and Tabu Search algorithms were used. As a basis for the research employing, historical data were accepted. Each order were given a priority, production time, profit and penalty for failure. Additionally, the machine failure risk was calculated based on empirical measurements. Simulations of several subsequent working weeks were performed in order to analyse the results obtained thanks to the suggested methods and to compare them with the results presently reached by the company.

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References

  1. Betz, F.: Strategic business models. Eng. Manage. J. 14(1), 21–28 (2002)

    Article  Google Scholar 

  2. Bożejko, W., Uchroński, M., Wodecki, M.: Parallel tabu search algorithm with uncertain data for the flexible job shop problem. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds.) ICAISC 2016. LNCS, vol. 9693, pp. 419–428. Springer, Cham (2016)

    Google Scholar 

  3. Brandão, J.: A tabu search algorithm for the open vehicle routing problem. Eur. J. Oper. Res. 157(3), 552–564 (2004)

    Article  MathSciNet  Google Scholar 

  4. Burduk, A., Musiał, K.: Genetic algorithm adoption to transport task optimization. In: Graña, M., López-Guede, J.M., Etxaniz, O., Herrero, Á., Quintián, H., Corchado, E. (eds.) ICEUTE/SOCO/CISIS -2016. AISC, vol. 527, pp. 366–375. Springer, Cham (2017)

    Google Scholar 

  5. Burduk, A., Musiał, K.: Optimization of chosen transport task by using generic algorithms. In: Saeed, K., Homenda, W. (eds.) CISIM 2016. LNCS, vol. 9842, pp. 197–205. Springer, Cham (2016)

    Google Scholar 

  6. Cordeau, J.F., Gendreau, M., Laporte, G.: A tabu search heuristic for periodic and multi-depot vehicle routing problems. Networks 30(2), 105–119 (1997)

    Article  Google Scholar 

  7. DeVore, R.A., Temlyakov, V.N.: Some remarks on greedy algorithms. Adv. Comput. Math. 5, 173–187 (1996)

    Article  MathSciNet  Google Scholar 

  8. Gola A., Kłosowski G., Application of fuzzy logic and genetic algorithms in automated works transport organization. In: Advances in Intelligent Systems and Computing, vol. 620, pp. 29–36 (2018)

    Google Scholar 

  9. Górnicka, D., Markowski, M., Burduk, A.: Optimization of production organization in a packaging company by ant colony algorithm. In: Intelligent Systems in Production Engineering and Maintenance, ISPEM 2017. Advances in Intelligent Systems and Computing, pp. 336–346. Springer (2018)

    Google Scholar 

  10. Grabowski, J., Pempera, J.: New block properties for the permutation flow shop problem with application in tabu search. J. Oper. Res. Soc. 52(2), 210–220 (2001)

    Article  Google Scholar 

  11. Grabowski, J., Wodecki, M.: A very fast tabu search algorithm for the permutation flow shop problem with makespan criterion. Comput. Oper. Res. 31(11), 1891–1909 (2004)

    Article  MathSciNet  Google Scholar 

  12. Guillén, G., Badell, M., Espuña, A., Puigjaner, L.: Simultaneous optimization of process operations and financial decisions to enhance the integrated planning/scheduling of chemical supply chains. Comput. Chem. Eng. 30(3), 421–436 (2006)

    Article  Google Scholar 

  13. Ho, W., Xu, X., Dey, P.K.: Multi-criteria decision making approaches for supplier evaluation and selection: a literature review. Eur. J. Oper. Res. 202(1), 16–24 (2010)

    Article  Google Scholar 

  14. Jones, D.F., Mirrazavi, S.K., Tamiz, M.: Multi-objective meta-heuristics: an overview of the current state-of-the-art. Eur. J. Oper. Res. 137(1), 1–9 (2002)

    Article  Google Scholar 

  15. Kahraman, C., Engin, O., Kaya, I., Öztürk, R.E.: Multiprocessor task scheduling in multistage hybrid flow-shops: a parallel greedy algorithm approach. Appl. Soft Comput. 10, 1293–1300 (2010)

    Article  Google Scholar 

  16. Kotowska, J., Markowski, M., Burduk, A.: Optimization of the supply of components for mass production with the use of the ant colony algorithm. In: Intelligent Systems in Production Engineering and Maintenance, ISPEM 2017. Advances in Intelligent Systems and Computing, pp. 347–357. Springer (2018)

    Google Scholar 

  17. Musiał, K., Kotowska, J., Górnicka, D., Burduk, A.: Tabu search and greedy algorithm adaptation to logistic task. In: Saeed, K., Homenda, W., Chaki, R. (eds.) Computer Information Systems and Industrial Management, CISIM 2017. Lecture Notes in Computer Science, vol. 10244, pp. 39–49. Springer, Cham (2017)

    Chapter  Google Scholar 

  18. Papageorgiou, L.G.: Supply chain optimisation for the process industries: advances and opportunities. Comput. Chem. Eng. 33(12), 1931–1938 (2009)

    Article  Google Scholar 

  19. Pohekar, S.D., Ramachandran, M.: Application of multi-criteria decision making to sustainable energy planning - a review. Renew. Sustain. Energy Rev. 8, 365–381 (2004)

    Article  Google Scholar 

  20. Zhang, Z., Schwartz, S., Wagner, L., Miller, W.: A greedy algorithm for aligning DNA sequences. J. Comput. Biol. 7, 203–214 (2000)

    Article  Google Scholar 

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Correspondence to Anna Burduk .

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Musiał, K., Kochańska, J., Burduk, A. (2019). Rationalization of Production Order Execution with Use of the Greedy and Tabu Search Algorithms. In: Graña, M., et al. International Joint Conference SOCO’18-CISIS’18-ICEUTE’18. SOCO’18-CISIS’18-ICEUTE’18 2018. Advances in Intelligent Systems and Computing, vol 771. Springer, Cham. https://doi.org/10.1007/978-3-319-94120-2_24

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