Reliability Optimization Problems using Adaptive Genetic Algorithm and Improved Particle Swarm Optimization

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YoungSu Yun (Editor)
Chosun University, Dong-gu, Republic of Korea

Series: Mathematics Research Developments
BISAC: MAT000000

This new book discusses why several reliability optimization problems are considered to be optimized. For the optimization, a hybrid approach using adaptive genetic algorithm (aGA) and improved particle swarm optimization (iPSO) is proposed. For the aGA, an adaptive scheme is incorporated into genetic algorithm (GA) loop and it adaptively regulates crossover and mutation rates during genetic search process. For the iPSO, a conventional PSO is improved and it is applied to the hybrid approach.

Therefore, the proposed hybrid approach takes an advantage of compensatory property of the aGA and the iPSO. For proving the performance of the proposed hybrid approach, conventional hybrid algorithms using GA and PSO are presented and their performances are compared with that of the proposed hybrid algorithm using several reliability optimization problems which have been often used in many conventional studies. (Imprint: Nova)

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Table of Contents

Table of Contents

ABSTRACT

1. INTRODUCTION

2. RELIABILITY OPTIMIZATION PROBLEMS

3. HYBRID APPROACH USING IGA AND IPSO

4. NUMERICAL EXAMPLES

5. CONCLUSION

6. REFERENCES

INDEX

Additional information

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