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Staffing decisions for heterogeneous workers with turnover
Authors:Hyun-Soo Ahn  Rhonda Righter  J George Shanthikumar
Institution:(1) Operations and Management Science, University of Michigan Business School, 701 Tappan St, Ann Arbor, MI 48109-1234, USA;(2) Department of Industrial Engineering and Operations Research, University of California, Berkeley, CA 94720, USA
Abstract:In this paper we consider a firm that employs heterogeneous workers to meet demand for its product or service. Workers differ in their skills, speed, and/or quality, and they randomly leave, or turn over. Each period the firm must decide how many workers of each type to hire or fire in order to meet randomly changing demand forecasts at minimal expense. When the number of workers of each type can by continuously varied, the operational cost is jointly convex in the number of workers of each type, hiring and firing costs are linear, and a random fraction of workers of each type leave in each period, the optimal policy has a simple hire- up-to/fire-down-to structure. However, under the more realistic assumption that the number of workers of each type is discrete, the optimal policy is much more difficult to characterize, and depends on the particular notion of discrete convexity used for the cost function. We explore several different notions of discrete convexity and their impact on structural results for the optimal policy.
Keywords:optimal staffing  discrete optimization  dynamic programming  multimodularity
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