| 引用本文: | 陈琪锋,戴金海.多目标的分布式协同进化MDO算法.[J].国防科技大学学报,2002,24(4):12-15.[点击复制] |
| CHEN Qifeng,DAI Jinhai.Multiobjective Distributed Coevolutionary Multidisciplinary Design Optimization[J].Journal of National University of Defense Technology,2002,24(4):12-15[点击复制] |
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| 多目标的分布式协同进化MDO算法 |
| 陈琪锋, 戴金海 |
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(国防科技大学 航天与材料工程学院，湖南 长沙 410073)
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| 摘要: |
| 通过引入非优超排序和排挤的多目标处理机制，将分布式协同进化MDO算法的能力扩展到多目标的多学科设计优化问题。多目标的分布式协同进化MDO算法在保持各学科充分自治和各学科并行设计优化协同的基础上，通过一次运行即可获得具有良好分布的多个Pareto最优解，逼近整个Pareto最优前沿。应用于导弹气动/发动机/控制三学科两目标设计优化问题，与约束法计算结果的对比表明算法能够有效逼近该问题的Pareto最优前沿，为设计决策提供了丰富的信息。 |
| 关键词: 导弹设计 多学科设计优化 多目标优化 进化计算 协同进化算法 分布式计算 |
| DOI： |
| 投稿日期：2002-03-10 |
| 基金项目: |
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| Multiobjective Distributed Coevolutionary Multidisciplinary Design Optimization |
| CHEN Qifeng, DAI Jinhai |
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(College of Aerospace and Materials Engineering, National Univ. of Defense Technology, Changsha 410073, China)
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| Abstract: |
| By introducing multiobjective handling mechanism of nondominated sorting and crowding, ability of distributed coevolutionary multidisciplinary design optimization algorithm is extended to multiobjective multidisciplinary design optimization (MDO) problems. The multiobjective distributed coevolutionary MDO approach maintains sufficient disciplinary autonomy, exploits synergism of disciplinary concurrent design optimizations, meanwhile it obtains a set of well distributed Pareto optimal solutions and makes a good approximation of the whole Pareto optimal front in one single run. It is applied to a missile design optimization problem with two system objectives and three disciplines－aerodynamic, engine, and control. Comparison with the results of the constraint method indicates that the multiobjective coevolutionary MDO approach can effectively approximate Pareto optimal front of the ploblem, providing plenty of information for design decision making. |
| Keywords: missile design multidisciplinary design optimization multiobjective optimization evolutionary computation coevolutionary algorithms distributed computing |
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