Scheduling Jobs Sharing Multiple Resources under Uncertainty: A Stochastic Programming Approach
نویسندگان
چکیده
We formulate a two-stage stochastic integer program to determine an optimal schedule for jobs requiring multiple classes of resources under uncertain processing times, due dates, resource consumption and availabilities. We allow temporary resource capacity expansion for a penalty. Potential applications of this model include team scheduling problems that arise in service industries such as engineering consulting and operating room scheduling. We develop an exact solution method based on Benders decomposition for problems with a moderate number of scenarios. Then we embed Benders decomposition within a sampling-based solution method for problems with a large number of scenarios. We modify a sequential sampling procedure to allow for approximate solution of integer programs and prove desired properties. We compare the solution methodologies on a set of test problems. Several algorithmic enhancements are added to improve efficiency.
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