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Capacitated Dynamic Lot Sizing with Capacity Acquisition

Author

Listed:
  • Hongyan Li

    (Aarhus School of Business, Aarhus University, Denmark)

  • Joern Meissner

    (Department of Management Science, Lancaster University Management School)

Abstract

One of the fundamental problems in operations management is determining the optimal investment in capacity. Capacity investment consumes resources and the decision, once made, is often irreversible. Moreover, the available capacity level affects the action space for production and inventory planning decisions directly. In this paper, we address the joint capacitated lot sizing and capacity acquisition problem. The firm can produce goods in each of the finite periods into which the production season is partitioned. Fixed as well as variable production costs are incurred for each production batch, along with inventory carrying costs. The production per period is limited by a capacity restriction. The underlying capacity must be purchased up front for the upcoming season and remains constant over the entire season. We assume that the capacity acquisition cost is smooth and convex. For this situation, we develop a model which combines the complexity of time-varying demand and cost functions and of scale economies arising from dynamic lot-sizing costs with the purchase cost of capacity. We propose a heuristic algorithm that runs in polynomial time to determine a good capacity level and corresponding lot sizing plan simultaneously. Numerical experiments show that our method is a good trade-off between solution quality and running time.

Suggested Citation

  • Hongyan Li & Joern Meissner, 2005. "Capacitated Dynamic Lot Sizing with Capacity Acquisition," Working Papers MRG/0005, Department of Management Science, Lancaster University, revised Mar 2010.
  • Handle: RePEc:lms:mansci:mrg-0005
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    More about this item

    Keywords

    supply chain management; lot sizing; capacity; approximation; heuristics;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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