| Immune Genetic Algorithm for Optimal Design |
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| 引用本文： | 杨建国,李蓓智,项前. Immune Genetic Algorithm for Optimal Design[J]. 东华大学学报(英文版), 2002, 19(4) |
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| 作者姓名： | 杨建国 李蓓智 项前 |
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| 作者单位： | College of Mechanical Engineering，Dong Hua University，Shanghai，200051，College of Mechanical Engineering，Dong Hua University，Shanghai，200051，College of Mechanical Engineering，Dong Hua University，Shanghai，200051 |
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| 基金项目： | Shanghai Natural Science Foundation(01ZF14004) |
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| 摘 要： | A computing model employing the immune and genetic algorithm (IGA) for the optimization of part design is presented. This model operates on a population of points in search space simultaneously, not on just one point. It uses the objective function itself, not derivative or any other additional information and guarantees the fast convergence toward the global optimum. This method avoids some weak points in genetic algorithm, such as inefficient to some local searching problems and its convergence is too early. Based on this model, an optimal design support system (IGBODS) is developed. IGBODS has been used in practice and the result shows that this model has great advantage than traditional one and promises good application in optimal design.
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Immune Genetic Algorithm for Optimal Design |
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| YANG Jian-guo,LI Bei-zhi,XIANG Qian. Immune Genetic Algorithm for Optimal Design[J]. Journal of Donghua University, 2002, 19(4) |
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| Authors: | YANG Jian-guo LI Bei-zhi XIANG Qian |
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| Affiliation: | College of Mechanical Engineering, Dong Hua University, Shanghai, 200051 |
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| Abstract: | A computing model employing the immune and genetic algorithm (IGA) for the optimization of part design is presented. This model operates on a population of points in search space simultaneously, not on just one point. It uses the objective function itself, not derivative or any other additional information and guarantees the fast convergence toward the global optimum. This method avoids some weak points in genetic algorithm, such as inefficient to some local searching problems and its convergence is too early. Based on this model, an optimal design support system (IGBODS) is developed. IGBODS has been used in practice and the result shows that this model has great advantage than traditional one and promises good application in optimal design. |
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| Keywords: | automation artificial immune system (AIS) Optimal design evolutionary algorithm genetic algorithm |
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