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.