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A Study on Genetic Algorithm of Concurrent Spare Part Selection for Imported Weapon Systems  

Cho, Hyun-Ki (Dept. of Industrial and Information Systems Engineering, Seoul National University of Technology)
Kim, Woo-Je (Dept. of Industrial and Information Systems Engineering, Seoul National University of Technology)
Publication Information
Journal of Korean Institute of Industrial Engineers / v.36, no.3, 2010 , pp. 164-175 More about this Journal
Abstract
In this study, we developed a genetic algorithm to find a near optimal solution of concurrent spare parts selection for the operational time period with limited information of weapon systems purchased from overseas. Through the analysis of time profiles related with system operations, we first define the optimization goal which maintains the expected system operating rate under the budget restrictions, and the number of failures and the lead time for each spare part are used to calculate the estimated total down time of the system. The genetic algorithm for CSP selection shows that the objective function minimizes the estimated total down time of systems with satisfying the restrictions. The method provided by this study can be applied to the generalized model of CSP selection for the systems purchased from overseas without provision of their full structure and adequate information.
Keywords
Genetic Algorithm; Concurrent Spare Part; Estimated Total Down Time; Optimal Solution;
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