论文部分内容阅读
针对约束优化问题,提出了一类将种群中的个体分类排序的思想.算法的特点在于:先将种群中的解分为可行解和不可行解两类,然后分别按照不同的标准排序.由于很多约束优化问题的最优解位于可行域的边界上或附近,所以排序时并不认为可行解一定优于不可行解.基于此分类排队思想,特别设计了只允许同等级个体进行交叉的新的交叉算子,称之为同等级交叉算子,以及基于一维搜索的变异算子.算法同时采用了保证固定比例不可行解的自适应策略.4个标准测试函数的数值仿真结果验证了算法的有效性.
Aiming at the constraint optimization problem, a kind of thought is put forward to sort the individuals in the population.The characteristics of the algorithm are as follows: First, the solution of the population is divided into two kinds: feasible solution and infeasible solution, and then sorted according to different criteria Many constrained optimization problems are located at or near the boundary of the feasible region, so the feasible solutions are not considered to be better than infeasible solutions at the time of sorting. Based on this classification queuing idea, a new design is only designed to allow individuals at the same level to cross Crossover operator is called the same level crossover operator and mutation operator based on one-dimensional search.The algorithm also adopts an adaptive strategy to ensure a fixed proportion of infeasible solutions.The numerical simulation results of the four standard test functions verify The effectiveness of the algorithm.