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West Bengal, India

Sahoo L.,Raniganj Girls College | Banerjee A.,Asansol Engineering College | Bhunia A.K.,University of Burdwan | Chattopadhyay S.,Jadavpur University
Swarm and Evolutionary Computation

This paper deals with the development of an efficient hybrid approach based on genetic algorithm and particle swarm optimization for solving mixed integer nonlinear reliability optimization problems in series, series-parallel and bridge systems. This approach maximizes the overall system reliability subject to the nonlinear resource constraints arising on system cost, volume and weight. To meet these purposes, a novel hybrid algorithm with the features of advanced genetic algorithm and particle swarm optimization has been developed for determining the best found solutions. To test the capability and effectiveness of the proposed algorithm, three numerical examples have been solved and the computational results have been compared with the existing ones. From comparison, it is observed that the values of the system reliability are better than the existing results in all three examples. Moreover, the values of average computational time and standard deviation are better than the same of similar studies available in the existing literature. The proposed approach would be very helpful for reliability engineers/practitioners for better understanding about the system reliability and also to reach a better configuration. © 2014 Elsevier B.V. Source

Bhunia A.K.,University of Burdwan | Sahoo L.,Raniganj Girls College
Studies in Computational Intelligence

The objective of this chapter is to develop and solve the reliability optimization problems of series-parallel, parallel-series and complicated system considering the reliability of each component as interval valued number. For optimization of system reliability and system cost separately under resource constraints, the corresponding problems have been formulated as constrained integer/mixed integer programming problems with interval objectives with the help of interval arithmetic and interval order relations. Then the problems have been converted into unconstrained optimization problems by two different penalty function techniques. To solve these problems, two different real coded genetic algorithms (GAs) for interval valued fitness function with tournament selection, whole arithmetical crossover and non-uniform mutation for floating point variables, uniform crossover and uniform mutation for integer variables and elitism with size one have been developed. To illustrate the models, some numerical examples have been solved and the results have been compared. As a special case, taking lower and upper bounds of the interval valued reliabilities of component as same the corresponding problems have been solved and the results have been compared with the results available in the existing literature. Finally, to study the stability of the proposed GAs with respect to the different GA parameters (like, population size, crossover and mutation rates), sensitivity analyses have been shown graphically. © 2011 Springer-Verlag Berlin Heidelberg. Source

Sahoo L.,Raniganj Girls College | Bhunia A.K.,University of Burdwan | Kapur P.K.,University of Delhi
Computers and Industrial Engineering

In most of the real world design or decision making problems involving reliability optimization, there are simultaneous optimization of multiple objectives such as the maximization of system reliability and the minimization of system cost, weight and volume. In this paper, our goal is to solve the constrained multi-objective reliability optimization problem of a system with interval valued reliability of each component by maximizing the system reliability and minimizing the system cost under several constraints. For this purpose, four different multi-objective optimization problems have been formulated with the help of interval mathematics and our newly proposed order relations of interval valued numbers. Then these optimization problems have been solved by advanced genetic algorithm and the concept of Pareto optimality. Finally, to illustrate and also to compare the results, a numerical example has been solved. Source

Pandit D.,Variable Energy Cyclotron Center | Dey B.,Variable Energy Cyclotron Center | Mondal D.,Variable Energy Cyclotron Center | Mukhopadhyay S.,Variable Energy Cyclotron Center | And 4 more authors.
Physical Review C - Nuclear Physics

The first systematic study of the correlation between the experimental giant dipole resonance (GDR) width and the average deformation Œ of the nucleus at finite excitation is presented for the mass region A∼59 to 208. We show that the width of the GDR (Γ) and the quadrupole deformation of the nucleus do not follow a linear relation, as predicted earlier, owing to the GDR-induced quadrupole moment, and the correlation also depends on the mass of the nuclei. The different empirical values of Œ Œ extracted from the experimental GDR width match exceptionally well with the thermal shape fluctuation model. As a result, this universal correlation between Œ Œ and Γ provides a direct experimental probe to determine the nuclear deformation at finite temperature and angular momentum over the entire mass region. © 2013 American Physical Society. Source

Pandit D.,Variable Energy Cyclotron Center | Mukhopadhyay S.,Variable Energy Cyclotron Center | Bhattacharya S.,Darjeeling Government College | Pal S.,Variable Energy Cyclotron Center | And 2 more authors.
Physics Letters, Section B: Nuclear, Elementary Particle and High-Energy Physics

The energy spectrum of the high energy γ-rays in coincidence with the prompt γ-rays has been measured for the spontaneous fission of 252Cf. The nucleus-nucleus coherent bremsstrahlung of the accelerating fission fragments is observed and the result has been substantiated with a theoretical calculation based on the Coulomb acceleration model. The width of the giant dipole resonance (GDR) decay from the excited fission fragments has been extracted for the first time and compared with the thermal shape fluctuation model (TSFM) in the liquid drop formalism. The extracted GDR width is significantly smaller than the predictions of TSFM. © 2010 Elsevier B.V. All rights reserved. Source

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