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A GRASP algorithm for Quota sequences with minimum work overload and forced interruption of operations in a mixed-product assembly line

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Abstract

We present a GRASP algorithm to solve a problem that involves the sequencing of mixed products in an assembly line. The objective of the problem is to obtain a manufacturing sequence of models that generates a minimum work overload with a forced interruption of operations, which is regular in production, and in which, the production mix maintains the Quota property in the whole sequence. The implemented GRASP is compared with other procedures using instances of a case study of the Nissan engine manufacturing plant in Barcelona.

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References

  1. Yano, C.A., Rachamadugu, R.: Sequencing to minimize work overload in assembly lines with product options. Manag. Sci. 37(5), 572–586 (1991). https://doi.org/10.1287/mnsc.37.5.572

    Article  Google Scholar 

  2. Bolat, A., Yano, C.A.: Scheduling algorithms to minimize utility work at a single station on a paced assembly line. Prod. Plan. Control 3(4), 393–405 (1992). https://doi.org/10.1080/09537289208919409

    Article  Google Scholar 

  3. Tsai, L.H.: Mixed-model sequencing to minimize utility work and the risk of conveyor stoppage. Manag. Sci. 41(3), 485–495 (1995). https://doi.org/10.1287/mnsc.41.3.485

    Article  MATH  Google Scholar 

  4. Boysen, N., Fliedner, M., Scholl, A.: Sequencing mixed-model assembly lines: survey, classification and model critique. Eur. J. Oper. Res. 192(2), 349–373 (2009). https://doi.org/10.1016/j.ejor.2007.09.013

    Article  MathSciNet  MATH  Google Scholar 

  5. Scholl, A., Klein, R., Domschke, W.: Pattern based vocabulary building for effectively sequencing mixed-model assembly lines. J. Heuristics 4(4), 359–381 (1998). https://doi.org/10.1023/A:1009613925523

    Article  MATH  Google Scholar 

  6. Bautista, J., Cano, A.: Solving mixed model sequencing problem in assembly lines with serial workstations with work overload minimisation and interruption rules. Eur. J. Oper. Res. 210(3), 495–513 (2011). https://doi.org/10.1016/j.ejor.2010.022

    Article  MATH  Google Scholar 

  7. Bautista, J., Alfaro-Pozo, R., Batalla-García, C.: GRASP for sequencing mixed models in an assembly line with work overload, useless time and production regularity. Prog. Artif. Intell. 5(1), 27–33 (2016). https://doi.org/10.1007/s13748-015-0071-z

    Article  Google Scholar 

  8. Bautista, J., Cano, A., Alfaro, R.: Modeling and solving a variant of the mixed-model sequencing problem with work overload minimisation and regularity constraints. An application in Nissan’s Barcelona Plant. Expert Syst. Appl. 39(12), 11001–11010 (2012). https://doi.org/10.1016/j.eswa.2012.03.024

    Article  Google Scholar 

  9. Bautista, J., Cano, A., Alfaro-Pozo, R.: A hybrid dynamic programming for solving a mixed-model sequencing problem with production mix restriction and free interruptions. Prog. Artif. Intell. 6(1), 27–39 (2017). https://doi.org/10.1007/s13748-016-0101-5

    Article  Google Scholar 

  10. Bautista, J., Alfaro-Pozo, R.: Free and regular mixed-model sequences by a linear program-assisted hybrid algorithm GRASP-LP. Prog. Artif. Intell. 6(2), 159–169 (2017). https://doi.org/10.1007/s13748-017-0110-z

    Article  Google Scholar 

  11. Monden, Y.: Toyota Production System: An Integrated Approach to Just-In-Time, 4th edn. Productivity Press, New York (2011)

    Google Scholar 

  12. Aigbedo, H., Monden, Y.: A parametric procedure for multicriterion sequence scheduling for just-in-time mixed-model assembly lines. Int. J. Prod. Res. 35, 2543–2564 (1997). https://doi.org/10.1080/002075497194651

    Article  MATH  Google Scholar 

  13. Fullerton, R.R., Kennedy, F.A., Widener, S.K.: Lean manufacturing and firm performance: the incremental contribution of lean management accounting practices. J. Oper. Manag. 32(7–8), 414–428 (2014). https://doi.org/10.1016/j.jom.2014.09.002

    Article  Google Scholar 

  14. Miltenburg, J.: Level schedules for mixed-model assembly lines in just-in-time production systems. Manag. Sci. 35(2), 192–207 (1989). https://doi.org/10.1287/mnsc.35.2.192

    Article  MATH  Google Scholar 

  15. Bautista, J., Cano, A., Alfaro, R., Batalla, C.: Impact of the production mix preservation on the ORV problem. In: Bielza, C., et al. (eds.) Advances in Artificial Intelligence. CAEPIA 2013. Lecture Notes in Computer Science, vol. 8109. Springer, Berlin (2013). https://doi.org/10.1007/978-3-642-40643-0_26

    Google Scholar 

  16. Feo, T.A., Resende, M.G.C.: Greedy randomized adaptive search procedures. J. Glob. Optim. 6(2), 109–133 (1995). https://doi.org/10.1007/BF01096763

    Article  MathSciNet  MATH  Google Scholar 

  17. Resende, M.G., Ribeiro, C.C.: Greedy randomized adaptive search procedures: advances, hybridizations, and applications. In: Gendreau, M., Potvin, J.Y. (eds.) Handbook of Metaheuristics. International Series in Operations Research & Management Science, vol. 146. Springer, Boston (2010). https://doi.org/10.1007/978-1-4419-1665-5_10

    Google Scholar 

  18. Bautista, J., Companys, R., Corominas, A.: Heuristics and exact algorithms for solving the Monden problem. Eur. J. Oper. Res. 88(1), 495–513 (1996). https://doi.org/10.1016/0377-2217(94)00165-0

    Article  MATH  Google Scholar 

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Acknowledgements

This work was funded by the Ministry of Economy and Competitiveness (Government of de Spain) through Project TIN2014-57497-P (FHI-SELM2).

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Correspondence to Joaquín Bautista.

Appendix I: Data of the set of instances Nissan-9Eng.I

Appendix I: Data of the set of instances Nissan-9Eng.I

See Tables 3 and 4.

Table 3 Processing times at normal activity \(\left( p_{i,k} \right) \) in seconds for the nine engine types \(( i\in I )\) in the 21 workstations \(\left( k\in K \right) \) of the set of instances Nissan-9Eng.I
Table 4 Daily demands by product and plan \(\left( d_{i{,}\varepsilon } \right) \) for the 23 instances Nissan-9Eng.I \((\varepsilon \in {\mathrm{E}})\)

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Bautista, J., Alfaro-Pozo, R. A GRASP algorithm for Quota sequences with minimum work overload and forced interruption of operations in a mixed-product assembly line. Prog Artif Intell 7, 197–211 (2018). https://doi.org/10.1007/s13748-018-0144-x

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