可用于有约束函数优化的竞赛争冠算法程序已基本完成,但肯定还有未发现的问题.请您试用,并提宝贵的意见和批评.谢谢!该程序是在自创的无约束优化的竞赛争冠算法(旧称竞技取冠算法)函数优化程序基础上,开发出来的有约束优化程序.程序采用罚函数法实现有约束优化的,但罚因子(惩罚系数)的处理方法有别于其它罚函数法.该程序证明这种惩罚系数处理方法是有效的.该法调整惩罚系数简单,粗放,一般应用默认值即可.该程序普适性较好,进化参数调整简单,不敏感,全局最优解的搜索能力较强,数据重现性(鲁棒性)较好,获得结果精度较高,不足是有时评价函数调用次数稍多些.<进化记录>.txt记录进化全程.其中有惩罚项值和约束值数据记录,有助于指导有约束优化的进行.可看出所得解是可行解或是不可行解?那些约束是激活的(stexp>=a变stexp-a>=0 或是 stexp<=b变stexp-b<=0观察)?-Can be used for constrained function optimization algorithm for the race program has basically completed the title race, but certainly there are no problems found. Please try and provide valuable advice and criticism. Thank you!

　The program is a self-designed race champion, unconstrained optimization algorithm (formerly known as competitive access crown algorithm) based on function optimization procedure, developed in a constrained optimization procedure. Program uses penalty function to achieve optimal binding, but the penalty factor (penalty factor) approach is different from other penalty function. The program proved such a penalty factor approach is valid. to adjust the penalty factor method is simple, extensive, general application of the default values can be. the program more universal Well, evolution parameter adjustment simple, sensitive, global optimal solutions of strong search capabilities, data reproducibility (robustness) better access to accurate result is sometimes