A Decision Support System for Solving Multi‐Objective Redundancy Allocation Problems |
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Authors: | Kaveh Khalili‐Damghani Amir‐Reza Abtahi Madjid Tavana |
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Affiliation: | 1. Department of Industrial Engineering, South‐Tehran Branch, Islamic Azad University, , Tehran, Iran;2. Department of Knowledge Engineering and Decision Sciences, Faculty of Economics Insinuations Management, University of Economic Sciences, , Tehran, Iran;3. Business Systems and Analytics, Lindback Distinguished Chair of Information Systems and Decision Sciences, La Salle University, , Philadelphia, PA, 19141 U.S.A. |
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Abstract: | The Redundancy Allocation Problem (RAP) is a reliability optimization problem in designing series‐parallel systems. The reliability optimization process is intended to select multiple components with appropriate levels of redundancy by maximizing the system reliability under some predefined constraints. Several methods have been proposed to solve the RAPs. However, most of these methods often treat RAP as a single objective problem of maximizing the system reliability (or minimizing the system design cost). We propose a Decision Support System for solving Multi‐Objective RAPs. Initially, we use the Technique for Order Performance by Similarity to Ideal Solution method to reduce the multiple objective dimensions of the problem. We then propose an efficient ε‐constraint method to generate non‐dominated solutions on the Pareto front. Finally, we use a Data Envelopment Analysis model to prune the non‐dominated solutions. A benchmark case is presented to assess the performance of the proposed system, demonstrate the applicability of the proposed framework, and exhibit the efficacy of the procedures and algorithms. Copyright © 2013 John Wiley & Sons, Ltd. |
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Keywords: | redundancy allocation problem multiple objective decision support system reliability ε ‐constraint method TOPSIS data envelopment analysis |
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