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Berkin Toktas, University of Washington, Industrial Engineering|
Joyce W. Yen, University of Washington, ADVANCE Center for Institutional Change
Zelda B. Zabinsky, University of Washington, Industrial Engineering
|Title:||A stochastic programming approach to resource-constrained assignment problems|
|Date of Acceptance:||17.05.2004|
Stochastic Programming E-Print Series |
|Editors:||Julie L. Higle; Werner Römisch; Surrajeet Sen|
|Complete Preprint:||pdf (urn:nbn:de:kobv:11-10059526)|
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|We address the resource-constrained generalizations of the assignment problem with uncertain resource capacities, where the resource capacities have an unknown distribution that can be sampled. We propose three stochastic programming-based formulations that can be used to solve this problem, and provide exact and approximate solution techniques for the resulting models. We also present numerical results for a large set of numerical problems. The results indicate that the solutions obtained using the stochastic programming approaches perform significantly better than those obtained using expected values of capacities in a deterministic solution strategy. In addition, stochastic-programming-based approximations are computationally as efficient as deterministic techniques.|
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