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Please use this identifier to cite or link to this item: http://repository.iitr.ac.in/handle/123456789/19812
Title: Fuzzy Multi-Objective Reliability Optimization of the Mixed Series-Parallel System Using Hybrid NSGA-II
Authors: Kumar H.
Yadav, Shiv Prasad
Pant M.
Sharma T.K.
Verma O.P.
Singla R.
Sikander A.
Published in: Advances in Intelligent Systems and Computing
Proceedings of 3rd International Conference on Soft Computing: Theories and Applications, SoCTA 2018
Abstract: Practically, reliability involved in the system design is enhanced with a reduction of other mutually conflicting objectives simultaneously such as cost, weight, volume, etc. Moreover, different types of uncertainty such as expert’s information character, qualitative statements, vagueness, incompleteness, and unclear system boundaries are typical in multi-objective decision-making of reliability. This paper proposes a hybrid NSGA-II for fuzzy multi-objective reliability optimization which comprises NSGA-II, local search strategy, and clustering technique. Local search strategy helps to update each Pareto-optimal solution after an NSGA-II simulation run which gives a better convergence near the true Pareto-optimal front while the clustering technique maintains a good diversity in the solutions set. Finally, the best compromise solution is achieved by using the fuzzy ranking method. The results obtained by the proposed methodology are then compared with popular elitist multi-objective evolutionary algorithms (MOEAs) namely NSGA-II and PESA-II as well as a multi-objective swarm technique known as MOPSO. A numerical example of the mixed series–parallel is given to show the effectiveness of the proposed approach.
Citation: Advances in Intelligent Systems and Computing, 2020, 479- 490
URI: https://doi.org/10.1007/978-981-15-0751-9_45
http://repository.iitr.ac.in/handle/123456789/19812
Issue Date: 2020
Publisher: Springer
Keywords: Clustering
Fuzzy set theory
Local search
NSGA-II
System reliability
Cluster analysis
Computation theory
Decision making
Evolutionary algorithms
Fuzzy sets
Local search (optimization)
Multiobjective optimization
Pareto principle
Reliability theory
Soft computing
Clustering
Local search
Multi objective decision
ISBN: 9.78981E+12
ISSN: 21945357
Author Scopus IDs: 57196390327
57209022284
Author Affiliations: Kumar, H., Department of Mathematics, Indian Institute of Technology Roorkee, Roorkee, 247667, India
Yadav, S.P., Department of Mathematics, Indian Institute of Technology Roorkee, Roorkee, 247667, India
Corresponding Author: Kumar, H.; Department of Mathematics, India; email: hemantkumar2654@gmail.com
Appears in Collections:Conference Publications [MA]

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