TOWARDS DECENTRALIZED DECISIONS FOR MANAGING PRODUCT TRANSITIONS IN SEMICONDUCTOR MANUFACTURING
2022 WINTER SIMULATION CONFERENCE (WSC), pp. 3442–3452.
Continuous renewal of the product portfolio through product transitions is crucial to semiconductor manufacturing firms. These decisions take place in a decentralized environment, where decisions by different functional units must be coordinated to optimize corporate performance. Starting from a centralized optimization model, we obtain decentralized models using Lagrangian relaxation, and explore the challenges encountered in formulating and solving these decentralized models. Although the Lagrangian approaches yield tight upper bounds on the optimal solution value, the structure of the dual solution renders the construction of a near-optimal feasible solution difficult, and fully separable decentralized models encounter significant problems in achieving convergence due to scaling issues. We present computational experiments that illustrate the difficulties involved, and discuss directions for future work.