一种求解冰壶比赛对阵多约束问题的逐层优化算法

摘要

冰壶比赛对阵编排问题是一个难于收敛的多约束优化问题.为此提出一种求解此类问题的逐层优化的单亲遗传算法.首先将待求解问题的多个约束进行分层;其次设计了靶向自交叉算子进行第一层优化以提高搜索效率,设计了定点-随机自交叉算子进行第二层优化以保持种群的多样性;最后,将改进的算法用于解决冰壶比赛对阵编排的多约束优化问题,构建了该问题的适应度函数.仿真实验表明,与粒子群算法和经典遗传算法相比,所提算法能够有效求解冰壶比赛对阵编排的多约束优化问题.%Curling-match design is a multi-constraint optimization problem which is hard to be converged.Therefore,a hierarchic optimization partheno-genetic algorithm is proposed.First,multiple constraint of the problem is layered;then,the targeted self-crossover operator is designed in the first layer optimization to ensure the convergence of the algorithm,while the fixed-random self-crossover operator is designed in the second layer optimization to maintain diversity of the population appropriately;finally,the proposed algorithm is used to solve the problem of curling-match design after building its fitness functions.Compared with the particle swarm algorithm and genetic algorithm,the simulation results demonstrate that the designed algorithm can solve the problem more efficiently.