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International Journal of Mathematical, Engineering and Management Sciences

ISSN: 2455-7749


A Genetic Algorithm Based Hybrid Approach for Reliability-Redundancy Optimization Problem of a Series System with Multiple-Choice

A Genetic Algorithm Based Hybrid Approach for Reliability-Redundancy Optimization Problem of a Series System with Multiple-Choice

Asoke Kumar Bhunia
Department of Mathematics, The University of Burdwan, Burdwan-713104, WB, India.

Avijit Duary
Department of Mathematics, Sir J. C. Bose School of Engineering, SKFGI, Hoogly -712139, WB, India.

Laxminarayan Sahoo
Department of Mathematics, Raniganj Girls Raniganj-713358, West Bengal, India.

DOI https://dx.doi.org/10.33889/IJMEMS.2017.2.3-016

Received on December 10, 2016
  ;
Accepted on February 26, 2017

Abstract

The goal of this paper is to introduce an application of hybrid algorithm in reliability optimization problems for a series system with parallel redundancy and multiple choice constraints to maximize the system reliability subject to system budget and also to minimize the system cost subject to minimum level of system reliability. Both the problems are solved by using penalty function technique for dealing with the constraints and hybrid algorithm. In this algorithm, the well-known real coded Genetic Algorithm is combined with Self-Organizing Migrating Algorithm. As special cases, both the problems are formulated and solved considering single component without redundancy. Finally, the proposed approach is illustrated by some numerical examples and the computational results are discussed.

Keywords- Reliability-redundancy optimization, Multiple-choice constraints, Constrained integer nonlinear optimization, Genetic algorithm, Self-organizing migrating algorithm.

Citation

Bhunia, A. K., Duary, A., & Sahoo, L. (2017). A Genetic Algorithm Based Hybrid Approach for Reliability-Redundancy Optimization Problem of a Series System with Multiple-Choice. International Journal of Mathematical, Engineering and Management Sciences, 2(3), 185-212. https://dx.doi.org/10.33889/IJMEMS.2017.2.3-016.

Conflict of Interest

Acknowledgements

For this research, the first author would like to acknowledge the financial support provided by the Council of Scientific and Industrial Research (CSIR), New Delhi, India.

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