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Using FAHP-VIKOR for Operation Selection in the Flexible Job-Shop Scheduling Problem: A Case Study in Textile Industry

Part of the Lecture Notes in Computer Science book series (LNTCS,volume 10942)

Abstract

Scheduling of Flexible Job Shop Systems is a combinatorial problem which has been addressed by several heuristics and meta-heuristics. Nevertheless, the operation selection rules of both methods are limited to an ordered variant wherein priority-dispatching rules are not simultaneously deemed in the reported literature. Therefore, this paper presents the application of dispatching algorithm with operation selection based on Fuzzy Analytic Hierarchy Process (FAHP) and VIKOR methods while considering setup times and transfer batches. Dispatching, FAHP, and VIKOR algorithms are first defined. Second, a multi-criteria decision-making model is designed for operation prioritization. Then, FAHP is applied to calculate the criteria weights and overcome the uncertainty of human judgments. Afterwards, VIKOR is used to select the operation with the highest priority. A case study in the textile industry is shown to validate this approach. The results evidenced, compared to the company solution, a reduction of 61.05% in average delay.

Keywords

  • Flexible job shop problem
  • Scheduling
  • Dispatching algorithm
  • Fuzzy Analytic Hierarchy Process (FAHP)
  • VIKOR

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References

  1. Neufeld, J.S., Gupta, J.N.D., Buscher, U.: A comprehensive review of flowshop group scheduling literature (2016)

    Google Scholar 

  2. Ortiz, M., Neira, D., Jiménez, G., Hernández, H.: Solving flexible job-shop scheduling problem with transfer batches, setup times and multiple resources in apparel industry. In: Tan, Y., Shi, Y., Li, L. (eds.) ICSI 2016. LNCS, vol. 9713, pp. 47–58. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-41009-8_6

    CrossRef  Google Scholar 

  3. Neira Rodado, D., Escobar, J.W., García-Cáceres, R.G., Niebles Atencio, F.A.: A mathematical model for the product mixing and lot-sizing problem by considering stochastic demand. Int. J. Ind. Eng. Comput. 8(2), 237–250 (2016)

    Google Scholar 

  4. Landinez-Lamadrid, D.C., Ramirez-Ríos, D.G., Neira Rodado, D., Parra Negrete, K., Combita Niño, J.: Shapley Value: its Algorithms and Application to Supply Chains El valor de Shapley: sus Algoritmos y Aplicación en Cadenas de Suministro, Enero-Junio, vol. 13, no. 2, pp. 61–69 (2017)

    CrossRef  Google Scholar 

  5. Atencio, F.N., Prasca, A.B., Rodado, D.N., Casseres, D.M., Santiago, M.R.: A comparative approach of ant colony system and mathematical programming for task scheduling in a mineral analysis laboratory, vol. 9712 (2016)

    Google Scholar 

  6. Ortiz Barrios, M., Neira Rodado, D., Jiménez, G., López Meza, P.: Integration of dispatching algorithm and AHP-TOPSIS method for flexible job-shop scheduling problem: a case study from the apparel industry. Int. J. Control Theory Appl. (2016)

    Google Scholar 

  7. Conway, R.W., Maxwell, W.L.: Theory of Scheduling. Dover, New York (2003)

    MATH  Google Scholar 

  8. Melanie, M.: An Introduction to Genetic Algorithms Library of Congress Cataloging − in − Publication Data (1998)

    Google Scholar 

  9. Kumar, R., Jain, A.: Assessment of makespan performance for flexible process plans in job shop scheduling, pp. 1948–1953 (2015)

    Google Scholar 

  10. Calleja, G., Pastor, R.: A dispatching algorithm for flexible job-shop scheduling with transfer batches: an industrial application. Prod. Plan. Control 25(2), 93–109 (2014)

    CrossRef  Google Scholar 

  11. Dargi, A., Anjomshoae, A., Galankashi, M.R., Memari, A., Tap, M.B.M.: Supplier selection: a fuzzy-ANP approach. Procedia Comput. Sci. 31, 691–700 (2014)

    CrossRef  Google Scholar 

  12. Demir, Y., Kürşat İşleyen, S.: Evaluation of mathematical models for flexible job-shop scheduling problems. Appl. Math. Model. 37(3), 977–988 (2013)

    MathSciNet  CrossRef  Google Scholar 

  13. Zhang, G., Gao, L., Shi, Y.: An effective genetic algorithm for the flexible job-shop scheduling problem. Expert Syst. Appl. 38(4), 3563–3573 (2011)

    CrossRef  Google Scholar 

  14. Brucker, P., Schlie, R.: Job-shop scheduling with multi-purpose machines. Computing 45(4), 369–375 (1990)

    MathSciNet  CrossRef  Google Scholar 

  15. Genova, K., Kirilov, L., Guliashki, V.: A survey of solving approaches for multiple objective flexible job shop scheduling problems

    Google Scholar 

  16. Brandimarte, P.: Routing and scheduling in a flexible job shop by tabu search. Ann. Oper. Res. 41(3), 157–183 (1993)

    CrossRef  Google Scholar 

  17. Wu, Z.: Multi-agent workload control and flexible job shop scheduling. University of South Florida (2005)

    Google Scholar 

  18. Tanev, I.T., Uozumi, T., Morotome, Y.: Hybrid evolutionary algorithm-based real-world flexible job shop scheduling problem: application service provider approach. Appl. Soft Comput. 5(1), 87–100 (2004)

    CrossRef  Google Scholar 

  19. Pezzella, F., Morganti, G., Ciaschetti, G.: A genetic algorithm for the flexible job-shop scheduling problem. Comput. Oper. Res. 35(10), 3202–3212 (2008)

    CrossRef  Google Scholar 

  20. Low, C., Yip, Y., Wu, T.-H.: Modelling and heuristics of FMS scheduling with multiple objectives. Comput. Oper. Res. 33(3), 674–694 (2006)

    CrossRef  Google Scholar 

  21. Fattahi, P., Saidi Mehrabad, M., Jolai, F.: Mathematical modeling and heuristic approaches to flexible job shop scheduling problems. J. Intell. Manuf. 18(3), 331–342 (2007)

    CrossRef  Google Scholar 

  22. Saaty, T.L.: Decision making with dependence and feedback: the analytic network process, pp. 83–135. RWS Publications (2001)

    Google Scholar 

  23. Ortíz, M.A., Cómbita, J.P., Hoz, Á.L.A.D.L., Felice, F.D., Petrillo, A.: An integrated approach of AHP-DEMATEL methods applied for the selection of allied hospitals in outpatient service. Int. J. Med. Eng. Inform. 8(2), 87–107 (2016)

    CrossRef  Google Scholar 

  24. İç, Y.T., Yurdakul, M.: Development of a decision support system for machining center selection. Expert Syst. Appl. 36(2), 3505–3513 (2009)

    CrossRef  Google Scholar 

  25. Lee, S.H.: Using fuzzy AHP to develop intellectual capital evaluation model for assessing their performance contribution in a university. Expert Syst. Appl. 37(7), 4941–4947 (2010)

    CrossRef  Google Scholar 

  26. Zavadskas, E.K., Govindan, K., Antucheviciene, J., Turskis, Z.: Hybrid multiple criteria decision-making methods: a review of applications for sustainability issues. Economic Research-Ekonomska Istraživanja 29(1), 857–887 (2016)

    CrossRef  Google Scholar 

  27. Ertuğrul, Đ., Karakasoğlu, N.: Performance evaluation of Turkish cement firms with fuzzy analytic hierarchy process and TOPSIS methods. Expert Syst. Appl. 36(1), 702–715 (2009)

    CrossRef  Google Scholar 

  28. Opricovic, S., Tzeng, G.H.: Compromise solution by MCDM methods: a comparative analysis of VIKOR and TOPSIS. Eur. J. Oper. Res. 156(2), 445–455 (2004)

    CrossRef  Google Scholar 

  29. Barrios, M.A.O.: Teoría de restricciones y modelación PL como herramientas de decisión estratégica para el incremento de la productividad en la línea de toallas de una compañía del sector textil y de confecciones. Prospectiva 11(1), 21–30 (2013)

    CrossRef  Google Scholar 

  30. Gao, K.Z., Suganthan, P.N., Pan, Q.K., Chua, T.J., Cai, T.X., Chong, C.S.: Pareto-based grouping discrete harmony search algorithm for multi-objective flexible job shop scheduling. Inf. Sci. 289, 76–90 (2014)

    MathSciNet  CrossRef  Google Scholar 

  31. Yuan, Y., Xu, H.: An integrated search heuristic for large-scale flexible job shop scheduling problems. Comput. Oper. Res. 40(12), 2864–2877 (2013)

    MathSciNet  CrossRef  Google Scholar 

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Correspondence to Miguel Ortíz-Barrios .

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Ortíz-Barrios, M., Neira-Rodado, D., Jiménez-Delgado, G., Hernández-Palma, H. (2018). Using FAHP-VIKOR for Operation Selection in the Flexible Job-Shop Scheduling Problem: A Case Study in Textile Industry. In: Tan, Y., Shi, Y., Tang, Q. (eds) Advances in Swarm Intelligence. ICSI 2018. Lecture Notes in Computer Science(), vol 10942. Springer, Cham. https://doi.org/10.1007/978-3-319-93818-9_18

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  • DOI: https://doi.org/10.1007/978-3-319-93818-9_18

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