A Mixed-Integer Programming Approximation to the Stochastic Multistage Inventory Model
Abstract
The study was concerned with the essential question of how to address multiperiod inventory problems characterized by not unrealistic conditions for which modeling and solution procedures have not been developed. The research placed special emphasis on the application of deterministic mixed-integer programming models to multiperiod inventory problems characterized by changing costs and beta-distributed demands. The special concern for the mixed-integer programming model was prompted by the realization that, among all of the easy- to-use deterministic inventory models, the mixed-integer programming formulation is the only model that is amenable to the additional constraints and multiple- objective criteria that coincide with broadly conceived statements of inventory control. Through the combined usage of mixed-integer programming and computer simulation techniques, a method was developed whereby a first-period reorder policy that minimizes expected total inventory cost over a multiperiod planning horizon can be identified with a nominal investment in computer processing time. The analysis led to the conclusion that first-period policies obtained by using the mixed-integer programming model with expectations as periodic demand inputs are generally adequate under the conditions specified in the research and compare favorably with policies obtained from commonly used inventory models. (Author)
Document Details
- Document Type
- Technical Report
- Publication Date
- May 01, 1978
- Accession Number
- ADA056514
Entities
People
- Donald R. Edwards
Organizations
- Air Force Institute of Technology