Abstract
We propose a planning model for multiple products manufactured across multiple manufacturing facilities sharing similar production capabilities. The need for cross-facility capacity management is most evident in high-tech industries that have capital-intensive equipment and a short technology life cycle. Our model is based on an emerging practice in these industries where product managers from business units dictate manufacturing planning in facilities that are equipped to produce their products. We propose a multicommodity flow network model where each commodity represents a product and the network structure represents linked manufacturing facilities capable of producing the products. We analyze in depth the product-level (single-commodity, multi-facility) subproblem when the capacity constraints are relaxed. We prove that even the general-cost version of this uncapacitated subproblem is NP-complete. We develop a shortest-path algorithm for this problem and show that it achieves optimality under special cost structures. We analyze and pinpoint specific cases where the algorithm fails to produce optimal solutions. To solve the overall (multicommodity) planning problem we develop a Lagrangian decomposition scheme, which separates the planning decisions into a number of single-product, multi-facility subproblems and a resource subproblem. Through extensive computational testing, we demonstrate that the shortest path algorithm is an effective heuristic for the MIP subproblem, yielding high quality solutions with only a fraction (roughly 2%) of the computer time.
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Wu, S.D., Golbasi, H. (2002). Manufacturing Planning Over Alternative Facilities: Modeling, Analysis and Algorithms. In: Geunes, J., Pardalos, P.M., Romeijn, H.E. (eds) Supply Chain Management: Models, Applications, and Research Directions. Applied Optimization, vol 62. Springer, Boston, MA. https://doi.org/10.1007/0-306-48172-3_11
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DOI: https://doi.org/10.1007/0-306-48172-3_11
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