Solving binary-state multi-objective reliability redundancy allocation series-parallel problem using efficient epsilon-constraint, multi-start partial bound enumeration algorithm, and DEA

In this paper, a procedure based on efficient epsilon-constraint method and data envelopment analysis (DEA) is proposed for solving binary-state multi-objective reliability redundancy allocation series-parallel problem (MORAP). In first module, a set of qualified non-dominated solutions on Pareto fr...

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Bibliographic Details
Published in:Reliability engineering & system safety Vol. 103; pp. 35 - 44
Main Authors: Khalili-Damghani, Kaveh, Amiri, Maghsoud
Format: Journal Article
Language:English
Published: Oxford Elsevier Ltd 01.07.2012
Elsevier
Subjects:
Algorithms
Allocations
Applied sciences
Benchmarking
DEA
Decision theory. Utility theory
Enumeration
Exact sciences and technology
Mathematical models
Mathematics
Modules
Multi-objective redundancy allocation problem
Nonparametric inference
Operational research and scientific management
Operational research. Management science
Operations research
Pareto front
Probability and statistics
Redundancy
Reliability theory. Replacement problems
Sciences and techniques of general use
Statistics
ε-constraint method
Pareto front
DEA
ε-constraint method
Multi-objective redundancy allocation problem
Performance evaluation
Statistical analysis
Enumeration
Filtering
Pareto optimum
Decision making
Redundancy
Multiobjective programming
Non parametric method
Non parametric estimation
Modeling
Multi-objective redundancy allocation
Upper bound
problem
Efficiency
Metric
Reliability
Data envelopment analysis
ISSN:0951-8320, 1879-0836
Online Access:Get full text
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Summary:In this paper, a procedure based on efficient epsilon-constraint method and data envelopment analysis (DEA) is proposed for solving binary-state multi-objective reliability redundancy allocation series-parallel problem (MORAP). In first module, a set of qualified non-dominated solutions on Pareto front of binary-state MORAP is generated using an efficient epsilon-constraint method. In order to test the quality of generated non-dominated solutions in this module, a multi-start partial bound enumeration algorithm is also proposed for MORAP. The performance of both procedures is compared using different metrics on well-known benchmark instance. The statistical analysis represents that not only the proposed efficient epsilon-constraint method outperform the multi-start partial bound enumeration algorithm but also it improves the founded upper bound of benchmark instance. Then, in second module, a DEA model is supplied to prune the generated non-dominated solutions of efficient epsilon-constraint method. This helps reduction of non-dominated solutions in a systematic manner and eases the decision making process for practical implementations. ► A procedure based on efficient epsilon-constraint method and DEA was proposed for solving MORAP. ► The performance of proposed procedure was compared with a multi-start PBEA. ► Methods were statistically compared using multi-objective metrics.
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ISSN:0951-8320
1879-0836
DOI:10.1016/j.ress.2012.03.006