2020 journal article
Iterative combinatorial auctions for managing product transitions in semiconductor manufacturing
IISE TRANSACTIONS, 52(4), 413–431.
author keywords: Product transitions; Lagrangian relaxation; column generation; iterative combinatorial auctions; semiconductor manufacturing
TL;DR:
Computational results show that the ICA that uses column generation to update prices outperforms that using subgradient search, obtaining near-optimal corporate profit in low CPU times.
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UN Sustainable Development Goal Categories
12. Responsible Consumption and Production
(Web of Science)
Source: Web Of Science
Added: October 7, 2019
Abstract Successful management of product transitions in the semiconductor industry requires effective coordination of manufacturing and product development activities. Manufacturing units must meet demand for current products while also allocating capacity to product development units for prototype fabrication that will support timely introduction of new products into high-volume manufacturing. Knowledge of detailed operational constraints and capabilities is only available within each unit, precluding the use of a centralized planning model with complete information of all units. However, the decision support tools used by the individual units offer the possibility of a decentralized decision framework that uses these local models as components to rapidly obtain mutually acceptable, implementable solutions. We develop Iterative Combinatorial Auctions (ICAs) that achieve coordinated decisions for all units to maximize the firm’s profit while motivating all units to share information truthfully. Computational results show that the ICA that uses column generation to update prices outperforms that using subgradient search, obtaining near-optimal corporate profit in low CPU times.