Abstract

This paper presents a novel application of robust optimization (RO) in the context of optimal choices of product-dedicated and flexible capacities in a spatial setting. Specifically, we examine the impact of acquiring flexible production technologies on a firm's overall capacity utilization rates under demand uncertainty. Uncorrelated, negatively, and positively correlated demands are considered. We implement an efficient RO algorithm, which can solve large samples of robust min-max problems in a realistic amount of time. This paper examines the impact of three critical factors that lead to different capacity utilization and resource flexibility outcomes: the degree of solution robustness selected by the decision-maker to accommodate uncertain demand realizations, the flexible capacity costs relative to dedicated capacity costs, and the level of correlation between product demands. One of our results show that according to robust solutions, the total capacity may not be fully utilized because of the distinction between largest (in unit terms) and costliest demand realizations. The second result shows that increasing the proportion of flexible capacity can increase capacity utilization; however, our results report less than full utilization even when using flexible capacity only. We show that the optimal amount of flexible capacity, and its impact on overall capacity utilization rate substantially depends on demand correlation.

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