Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
5111729 | Omega | 2017 | 32 Pages |
Abstract
We propose a simulation-based solution framework for tackling the multi-objective inventory optimization problem. The goal is to find appropriate settings of reorder point and order quantity to minimize three objective functions simultaneously, which are the expected values of the total inventory cost, the average inventory level, and the frequency of inventory shortage. We develop new algorithms that can exploit statistically valid ranking and selection (R&S) procedures and the desirable mechanics of conventional multi-objective optimization techniques. Two simulation algorithms are proposed to be applied in different scenarios depending on the preference information that is revealed either during or after the actual optimization process. Experimental results are provided to evaluate the efficiency of the developed algorithms and other existing solution frameworks.
Related Topics
Social Sciences and Humanities
Business, Management and Accounting
Strategy and Management
Authors
Shing Chih Tsai, Sin Ting Chen,