کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
480451 | 1446079 | 2012 | 11 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Improving the computational efficiency of metric-based spares algorithms Improving the computational efficiency of metric-based spares algorithms](/preview/png/480451.png)
We propose a new heuristic algorithm to improve the computational efficiency of the general class of Multi-Echelon Technique for Recoverable Item Control (METRIC) problems. The objective of a METRIC-based decision problem is to systematically determine the location and quantity of spares that either maximizes the operational availability of a system subject to a budget constraint or minimizes its cost subject to an operational availability target. This type of sparing analysis has proven essential when analyzing the sustainment policies of large-scale, complex repairable systems such as those prevalent in the defense and aerospace industries. Additionally, the frequency of these sparing studies has recently increased as the adoption of performance-based logistics (PBL) has increased. PBL represents a class of business strategies that converts the recurring cost associated with maintenance, repair, and overhaul (MRO) into cost avoidance streams. Central to a PBL contract is a requirement to perform a business case analysis (BCA) and central to a BCA is the frequent need to use METRIC-based approaches to evaluate how a supplier and customer will engage in a performance based logistics arrangement where spares decisions are critical. Due to the size and frequency of the problem there exists a need to improve the efficiency of the computationally intensive METRIC-based solutions. We develop and validate a practical algorithm for improving the computational efficiency of a METRIC-based approach. The accuracy and effectiveness of the proposed algorithm are analyzed through a numerical study. The algorithm shows a 94% improvement in computational efficiency while maintaining 99.9% accuracy.
Highlight
► Developed an algorithm that improves the computational efficiency of METRIC-based problems.
► Results show a 94% improvement in computational efficiency while maintaining 99.9% accuracy.
► Relevant to business case analysis (BCA) and performance-based logistics (PBL) contracts.
Journal: European Journal of Operational Research - Volume 219, Issue 2, 1 June 2012, Pages 324–334