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Optimal level schedules for mixed-model, multi-level just-in-time assembly systems

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  • Wieslaw Kubiak
  • George Steiner
  • Julian Scott Yeomans

Abstract

Solving the level (or balanced) schedule problem is the most important scheduling goal for just-in-time production assembly systems. No previous methods have been presented for determining optimal balanced schedules in multi-level facilities. In this paper, it is shown that the multi-level, min-max problem is NP-hard in the strong sense. A dynamic programming algorithm (DP) is developed for both the min-max and min-sum problems which, for the first time, permits optimal schedules to be determined for large, multi-level problems. The time and space requirements of the DP are analyzed and several techniques for reducing the DP's computational requirements are described. A filtering scheme is proposed to eliminate dominated solutions from a problem's potentially vast state space. Extensive computational testing of the min-max algorithm is reported and the conclusions from this testing are presented. Copyright Kluwer Academic Publishers 1997

Suggested Citation

  • Wieslaw Kubiak & George Steiner & Julian Scott Yeomans, 1997. "Optimal level schedules for mixed-model, multi-level just-in-time assembly systems," Annals of Operations Research, Springer, vol. 69(0), pages 241-259, January.
    • Handle: RePEc:spr:annopr:v:69:y:1997:i:0:p:241-259:10.1023/a:1018985029260
    DOI: 10.1023/A:1018985029260
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    Cited by:

    1. Christian Billing & Florian Jaehn & Thomas Wensing, 2020. "Fair task allocation problem," Annals of Operations Research, Springer, vol. 284(1), pages 131-146, January.
    2. Zhu, Jin & Ding, Fong-Yuen, 2000. "A transformed two-stage method for reducing the part-usage variation and a comparison of the product-level and part-level solutions in sequencing mixed-model assembly lines," European Journal of Operational Research, Elsevier, vol. 127(1), pages 203-216, November.
    3. Amogh Bhosekar & Sandra Ekşioğlu & Tuğçe Işık & Robert Allen, 2023. "A discrete event simulation model for coordinating inventory management and material handling in hospitals," Annals of Operations Research, Springer, vol. 320(2), pages 603-630, January.
    4. Boysen, Nils & Fliedner, Malte & Scholl, Armin, 2009. "The product rate variation problem and its relevance in real world mixed-model assembly lines," European Journal of Operational Research, Elsevier, vol. 197(2), pages 818-824, September.
    5. Drexl, Andreas & Kimms, Alf, 1999. "Belastungsorientierte Just-in-Time Variantenfließfertigung," Manuskripte aus den Instituten für Betriebswirtschaftslehre der Universität Kiel 502, Christian-Albrechts-Universität zu Kiel, Institut für Betriebswirtschaftslehre.
    6. Boysen, Nils & Fliedner, Malte & Scholl, Armin, 2009. "Sequencing mixed-model assembly lines: Survey, classification and model critique," European Journal of Operational Research, Elsevier, vol. 192(2), pages 349-373, January.
    7. Mansouri, S. Afshin, 2005. "A Multi-Objective Genetic Algorithm for mixed-model sequencing on JIT assembly lines," European Journal of Operational Research, Elsevier, vol. 167(3), pages 696-716, December.
    8. Aigbedo, Henry, 2007. "An assessment of the effect of mass customization on suppliers' inventory levels in a JIT supply chain," European Journal of Operational Research, Elsevier, vol. 181(2), pages 704-715, September.
    9. Vergauwen, P.G.M.C. & Busser, K. & Rongen, P. & Verwaijen, R. & Vossen, D.J.L.H., 2001. "Cost accounting and pricing improvement at Helmond Print: using Xeikon digital colour printing equipment: a case study," Research Memorandum 028, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    10. Drexl, Andreas & Kimms, Alf, 1997. "Sequencing JIT mixed-model assembly lines under station load- and part usage-constraints," Manuskripte aus den Instituten für Betriebswirtschaftslehre der Universität Kiel 460, Christian-Albrechts-Universität zu Kiel, Institut für Betriebswirtschaftslehre.

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