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Technometrics
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Genetic Algorithms in Search, Optimization and Machine Learning
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An Accelerated Genetic Algorithm
Applied Intelligence
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Computers in Industry
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Evolutionary Computation
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IEEE Transactions on Evolutionary Computation
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IEEE Transactions on Evolutionary Computation
Engineering Applications of Artificial Intelligence
A concentration-based artificial immune network for multi-objective optimization
EMO'11 Proceedings of the 6th international conference on Evolutionary multi-criterion optimization
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Applied Soft Computing
Information Sciences: an International Journal
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Computers & Mathematics with Applications
A comparative study of population-based optimization algorithms for turning operations
Information Sciences: an International Journal
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Structural and Multidisciplinary Optimization
Information Sciences: an International Journal
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Computers and Industrial Engineering
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Information Sciences: an International Journal
Information Sciences: an International Journal
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Applied Soft Computing
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Advances in Engineering Software
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This paper describes an innovative optimization approach that offers significant improvements in performance over existing methods to solve shape optimization problems. The new approach is based on two-stages which are (1) Taguchi's robust design approach to find appropriate interval levels of design parameters (2) Immune algorithm to generate optimal solutions using refined intervals from the previous stage. A benchmark test problem is first used to illustrate the effectiveness and efficiency of the approach. Finally, it is applied to the shape design optimization of a vehicle component to illustrate how the present approach can be applied for solving shape design optimization problems. The results show that the proposed approach not only can find optimal but also can obtain both better and more robust results than the existing algorithm reported recently in the literature.