Learning complementarity and setup time reduction

https://doi.org/10.1016/S0305-0548(97)00072-5Get rights and content

Abstract

This article studies the effects of transmission of learning in setups for the multi-item capacitated lot-sizing problem. This learning complementarity affects the scheduling of the products and the resulting model considers simultaneous decisions about lot-sizing and sequencing in a nonlinear formulation. Learning complementarity favors frequent setups and lower inventories and reaches the zero-inventory schedules even at low levels of learning. Through the use of an example the following three scenarios are examined: (i) no transmission of learning, (ii) partial transmission of learning, and (iii) complete transmission of learning. The schedules of the three scenarios are compared and the computational complexity of the nonlinear integer model considering lot-sizing and sequencing issues is discussed.

References (24)

  • T.P. Wright

    Factors affecting the cost of airplanes

    Journal of Aeronautical Sciences

    (1936)
  • Y.E. Yelle

    The learning curve: Historical review and comprehensive survey

    Decision Sciences

    (1979)
  • Cited by (4)

    • Single-minute exchange of die (SMED): a state-of-the-art literature review

      2019, International Journal of Advanced Manufacturing Technology
    • An application of SMED methodology

      2011, World Academy of Science, Engineering and Technology
    • Simulating alternative production policies with sequence-dependent costs

      2001, International Journal of Production Research

    Eleni Pratsini is Assistant Professor in the Department of Decision Sciences and Management Information Systems at Miami University. She received her B.Sc. in Civil Engineering from Birminham University (U.K.), her M.B.A. from UCLA and her Ph.D. in Quantitative Analysis from the University of Cincinnati. Her research interests concern the application of mathematical programming models in production scheduling, computer simulation, and environmental analysis using quantitative methods.

    View full text