Improving the computational efficiency of metric-based spares algorithms

• Published in: European journal of operational research Vol. 219; no. 2; pp. 324 - 334
• Main Authors: Nowicki, David R., Randall, Wesley S., Ramirez-Marquez, Jose Emmanuel
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 01.06.2012; Elsevier; Elsevier Sequoia S.A
• Subjects: Accuracy; Algorithms; Applied sciences; Availability; Business; Computational efficiency; Decision analysis; Decision theory. Utility theory; Effectiveness studies; Efficiency; Exact sciences and technology; Firm modelling; Heuristic; Inventory; Logistics; Mathematical problems; Operational research; Operational research and scientific management; Operational research. Management science; Optimization; Outcome based contracting; Performance based logistics; Policies; Reliability theory. Replacement problems; Supply chain; Supply chain; Outcome based contracting; Performance based logistics; Inventory; Optimization; Logistics; Availability; Decision making; Maintenance cost; Aerospace industry; Supplier customer relationship; Revision; Heuristic method; Budget; Metric; Localization; Repair; Contract; Firm strategy; Large scale system
• ISSN: 0377-2217; 1872-6860
• DOI: 10.1016/j.ejor.2011.12.033

► 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. 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.