A novel algorithm is proposed to deal with both unconstrained and constrained numerical optimization problems.
针对数值优化问题，提出了组织进化数值优化算法。
Hence, constrained multiobjective and constrained numerical optimization problems are done in this thesis based on double populations.
基于双群体搜索机制分别对约束多目标优化问题和约束单目标优化问题进行了研究。
This work improves the capability of representing and dealing with data and extends the range of solving numerical optimization problems in DNA computing.
该工作可提高DNA计算中表示和处理数值的能力，扩展DNA计算求解最优化问题的范围。
The M-elite coevolutionary algorithm (MECA) is proposed for high-dimensional unconstrained numerical optimization problems based on the concept of coevolutionary algorithm and elitist strategy.
本文在其基础上考虑了每个零部件的需求量不同所带来的影响，提出了一种基于精英策略和自适应性的混合遗传算法。
Evolutionary Structural optimization (ESO) is a simple and robust numerical method for optimization problems applicable to various types of structures.
渐进结构拓扑优化(eso)是近年来兴起的一种解决各类结构优化问题的数值方法。
This method and the numerical solutions show that the method is also suitable for pure mathematical optimization problems with 0-1 discrete variables.
该方法对于纯数学的0 - 1离散变量优化的求解也适用，方法与数值都表明了这一点。
This method and the numerical solutions show that the method is also suitable for pure mathematical optimization problems with 0-1 discrete variables.
该方法对于纯数学的0 - 1离散变量优化的求解也适用，方法与数值都表明了这一点。
应用推荐