一种求解不等式约束下函数优化问题的新算法

一种求解不等式约束下函数优化问题的新算法 A New Algorithm for Solving Function Optimization Problems with Inequality Constraints 郭涛 GUO Tao 1 first-author 康立山 KANG Li\|shan 1 李艳 LI Yan 1 武汉大学软件工程国家重点实验室,武汉,430072 武汉大学软件工程国家重点实验室,武汉,430072 State Key Laboratory of Software Engineering Wuhan University State Key Laboratory of Software Engineering Wuhan University 提出了一种求解不等式约束下的函数优化问题的新算法． 算法设计思想来源于演化计算的群体搜索技术，但又不同于现存的任何一种演化算法． 对一些典型的约束优化问题测试结果表明：新算法结构的简单性，搜索的高效性，收敛的全局性，应用的广泛性，算法的鲁棒性及结果的精确性，都优于现存的演化算法． A new algorithm for solving function optimization problem with inequality constraints is proposed. The ideas for designing the algorithm come from evolutionary computation,but deffer from any of the existing evolutionary algorithms. Some typical test problems are solved by this algorithm. The results show that new algorithm is better than existing evelutionary algorithm in the simplicity of structures, the robustness of algorithms, the accuracy of solutions and the wide range of applications. 遗传算法 不等式约束 函数优化问题 genetic algorithm inequality constraint function optimization problem TP301.6 国家自然科学基金(61672102);国家863 计划资助 1999-05-01 2021-04-01 5