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Tytuł artykułu

Minimizing the Makespan and Total Tardiness in Hybrid Flow Shop Scheduling with Sequence-Dependent Setup Times

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The paper considers the production scheduling problem in a hybrid flow shop environment with sequence-dependent setup times and the objectives of minimizing both the makespan and the total tardiness. The multi-objective genetic algorithm is applied to solve this problem, which belongs to the non-deterministic polynomial-time (NP)-hard class. In the structure of the proposed algorithm, the initial population, neighborhood search structures and dispatching rules are studied to achieve more efficient solutions. The performance of the proposed algorithm compared to the efficient algorithm available in literature (known as NSGA-II) is expressed in terms of the data envelopment analysis method. The computational results confirm that the set of efficient solutions of the proposed algorithm is more efficient than the other algorithm.
Twórcy
  • Depart- ment of Technical and Engineering, Nowshahr Branch, Islamic Azad University, Karimi, Nowshahr, Iran
  • Department of Industrial Engineering, Central Tehran Branch, Islamic Azad University, Tehran, Iran
Bibliografia
  • Abyaneh S.H. and Zandieh M. (2012), Bi-objective hybrid flow shop scheduling with sequence-dependent setup times and limited buffers. The International Journal of Advanced Manufacturing Technology, Vol. 58, No. 1, pp. 309–325.
  • Chen T.-L., Cheng C.-Y. and Chou Y.-H. (2020), Multiobjective genetic algorithm for energy-efficient hybrid flow shop scheduling with lot streaming. Annals of Operations Research, Vol. 290, No. 1, pp. 813–836. DOI: 10.1007/s10479-018-2969-x.
  • Cho H.-M. and Jeong I.-J. (2017), A two-level method of production planning and scheduling for bi-objective reentrant hybrid flow shops. Computers & Industrial Engineering, Vol. 106, No. 3, pp. 174–181.
  • Collette Y. and Siarry P. (2003), Multiobjective optimization: Principles and case studies. Springer, Berlin Heidelberg New York.
  • Deb K., Pratap A., Agarwal S. and Meyarivan T. (2002), A fast and elitist multi-objective genetic algorithm: NSGA II. IEEE Transaction on Evolutionary Computation, Vol. 6, No. 2, pp. 182–197.
  • Dugardin F., Yalaoui F. and Amodeo L. (2010), New multi-objective method to solve reentrant hybrid flow shop scheduling problem. European Journal of Operational Research, Vol. 203, No. 1, pp. 22–31.
  • Ebrahimi M., Fatemi Ghomi S. and Karimi B. (2014), Hybrid flow shop scheduling with sequence dependent family setup time and uncertain due dates. Applied Mathematical Modelling, Vol. 38, No. 1, pp. 2490–2504.
  • Fadaei M. and Zandieh M., (2013), Scheduling a biobjective hybrid flow shop with sequence-dependent family setup times using metaheuristics. Arab Journal Science Engineering, Vol. 38, No. 8, pp. 2233–2244.
  • Kurz M.E. and Askin R.G., (2003), Scheduling flexible flow lines with sequence-dependent setup times. European Journal of Operational Research, Vol. 159, No. 1, pp. 66–82.
  • Li Z., Zhong R.Y., Barenji A.V., Liu J.J., Yu C.X. and Huang G.Q. (2019), Bi-objec-tive hybrid flow shop scheduling with common due date. Operational Research, Vol. 181, No. 9, pp. 1–26.
  • Mousavi S.M., Zandieh M. and Amiri M., (2011), An efficient bi-objective heuristic for scheduling of hybrid flow shops. International Journal of Advanced Manufacturing Technology, Vol. 54, No. 1, pp. 287-307.
  • Mousavi S.M., Mahdavi I., Rezaeian J. and Zandieh M. (2018), An efficient bi-ob-jective algorithm to solve re-entrant hybrid flow shop scheduling with learning effect and setup times. Operational Research, Vol. 18, No. 1, pp. 123–158.
  • Neufeld J.S., Schulz S. and Buscher U., (In Press), A systematic review of multi-objective hybrid flow shop scheduling. European Journal of Operational Research. DOI: 10.1016/j.ejor.2022.08.009.
  • Ruiz R. and Marato C., (2006), A genetic algorithm for hybrid flowshops with sequence dependent setup times and machine eligibility. European Journal of Operational Research, Vol. 169, No. 3, pp. 781–800.
  • Ruiz R. and Vázquez-Rodríguez J.A., (2010), The Hybrid Flow Shop Scheduling Problem. European Journal of Operational Research, Vol. 205, No. 1, pp. 1–18.
  • Ruiz-Torres A.J. and Lopez F.J., (2004), Using the FDH formulation of DEA to evaluate a multi-criteria problem in parallel machine scheduling. Computers and Industrial Engineering, Vol. 47, No. 2–3, pp. 107–121.
  • Zheng Q.-Q., Zhang Y., Tian H.-W., and He L.-J. (2021), An effective hybrid meta-heuristic for flexible flow shop scheduling with limited buffers and step-deteriorating jobs. Engineering Applications of Artificial Intelligence, Vol. 106, p. 104503.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-8a7d6fb5-906f-4649-a223-dc872fe98eee
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