Efficient post-optimization analysis procedure for the dynamic lot-sizing problem

Article Abstract:

A study is conducted to evaluate the development of efficient post-optimization analysis for the dynamic lot-sizing problem. The study assumes that the problem involves determination of the level of produced items which satisfies demand while reducing costs. The procedure which establishes a Wagner-Whitin solution is then considered. Results show that the proposed procedure can be applied by using a branch and bound algorithmic context.

Production planning

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Optimal setup time reduction for a single product with dynamic demands

Article Abstract:

A dynamic programming procedure for reducing setup times in the dynamic lot-sizing problem is studied. The dynamic programming procedure is shown to be efficient and capable of simultaneously determining optimal setup times and optimal production quantities. The proposed solution is more general than any of its predecessors and this generality allows its application as a building block for setup time reduction models.

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Multiple items procurement under stochastic nonstationary demands

Article Abstract:

The sequential decision problem known as constrained, multi-item, stochastic, nonstationary lot sizing problem is considered. Specifically, the stochastic programming concept of rolling planning horizons is employed to recast it as a multi-period static decision problem under risk. A branch and bound algorithm for solving a deterministic version of the stochastic program is also developed.

Operations research, Management science, Purchasing, Case studies, Stochastic programming

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