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Charles R. Sox
Assistant Professor
Department of Industrial Engineering
Auburn University
This research will develop mathematical models and solution procedures for dynamically planning and scheduling manufacturing and distribution inventories of multiple products with random demand and finite production capacity, and will develop benchmarks for evaluating the performance of these algorithms. The production capacity at each stage may be augmented in a given time period with overtime, an additional shift, etc . The distribution system may be a single finished goods warehouse or a two level system with a central warehouse and multiple, non-identical retailers. General demand distributions will be used, and these distributions may be non-stationary to account for seasonality and trend. Both fixed and variable costs will be considered throughout the system. The basic approach of the research will be to develop mathematical programming models of these planning and scheduling problems and to use optimization techniques to generate optimal or near-optimal solutions. Stochastic dynamic programming will be used to optimally solve some small problem instances. Stochastic programming will be used to solve some larger problem instances. Also, new formulations that use nonlinear and piecewise linear functions to model the impact of demand uncertainty on inventory costs will be developed and tested for extremely large problem instances.
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