| 引用本文: | 钱淑渠,叶永强,武慧虹,吴永武.目标约束融合的约束多目标免疫算法及性能评价准则[J].控制理论与应用,2016,33(1):113~127.[点击复制] |
| QIAN Shu-qu,YE Yong-qiang,WU Hui-hong,WU Yong-wu.A constrained multiobjective immune algorithm based on objective and constraint fusion and performance evaluation metric[J].Control Theory and Technology,2016,33(1):113~127.[点击复制] |
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| 目标约束融合的约束多目标免疫算法及性能评价准则 |
| A constrained multiobjective immune algorithm based on objective and constraint fusion and performance evaluation metric |
| 摘要点击 3175 全文点击 1030 投稿时间：2014-11-25 修订日期：2015-08-22 |
| 查看全文 查看/发表评论 下载PDF阅读器 |
| DOI编号 10.7641/CTA.2016.41090 |
| 2016,33(1):113-127 |
| 中文关键词 约束多目标 免疫优化 亲和力 性能准则 转移算子 |
| 英文关键词 constrained multiobjective immune optimization affinity performance metric transformation operator |
| 基金项目 国家自然科学基金项目(61304146,61473145), 贵州省科技计划基金项目(20152002), 贵州教育厅优秀科技创新人才奖励计划项目(2014255)资助. |
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| 中文摘要 |
| 免疫算法求解约束多目标优化问题时, 如何设计抗体的亲和力, 以及如何保持或提高种群的多样性为算法
设计的关键. 本文基于免疫系统的固有免疫和自适应免疫交互运行模式, 提出目标约束融合的并行约束多目标免疫
算法(parallel constrained multiobjective immune algorithm, PCMIOA). 利用支配度和浓度设计抗体的亲和力, 提出了
目标约束融合的评价方法, 增强了算法的收敛性. 借助基因重组中DNA片段的转移机制, 设计一种转移(transformation)
算子, 提高了种群的多样性. 针对已有性能评价准则存在的不足给出一种改进的支配范围评价准则. 数值实
验选用12个约束二目标和4个非约束三目标测试函数验证PCMIOA的优化性能, 并将其与3种著名的约束多目标算
法和5种非约束多目标算法进行比较. 结果表明: PCMIOA具有较强的优化性能. 与其他算法相比, PCMIOA所获
的Pareto最优前沿能较好的逼近真实Pareto最优前沿, 且分布较均匀. |
| 英文摘要 |
| How to design the affinity of an antibody and to maintain or improve the population diversity has always
been a key problem, when an immune algorithm is applied to solve constrained multi-objective optimization problems
(CMOPs). To solve this problem, we propose a parallel constrained multi-objective immune algorithm (PCMIOA) by
merging objectives and constraints, based on the interactive operation of innate immune and adaptive immune in the immune
system. In this algorithm, we define the affinity of an antibody by using the domination degree and density, and develop an
evaluation approach for assembled objectives and constraints, which accelerates the convergence of PCMIOA. In addition, a
transformation mechanism that occurs in the recombination process of DNA segment is presented to improve the population
diversity. An improved domination scope metric is developed in order to overcome the disadvantages of the existing ones.
PCMIOA is applied to solve a set of twelve two-objective CMOPs and four unconstrained three-objective test problems. The
experimental results indicate that PCMIOA is able to achieve a superior performance. The Pareto-optimal front obtained by
PCMIOA very well approximates the true Pareto-optimal front and exhibits a well-spread when compared to three modern
constrained multi-objective algorithms and five unconstrained multi-objective algorithms. |
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