基于网格支配的微型多目标遗传算法

提出了一种基于网格支配的微型多目标遗传算法，该算法在求解较多目标函数的优化问题时具有较好的收敛性和较高的计算效率。该算法引入网格支配概念并结合微型多目标遗传算法，在每一代进化种群中计算各个个体的网格值、网格拥挤距离和网格坐标点距离，根据网格支配分级和网格选择机制策略选取精英个体，并对其进行交叉和变异操作，使其朝前沿面收敛以获得Pareto最优解。4个测试函数和2个工程实例验证了该算法的有效性。

Micro Multi-objective Genetic Algorithm Based on Grid Domination

A micro multi-objective genetic algorithm was proposed herein based on grid domination to solve multi-objective optimization problems and it had good convergence and high computational efficiency. The method combined with the concept of the grid dominance and micro multi-objective genetic algorithm. In each generation, the grid value, the grid crowding distance and grid coordinate point distance of every individual were calculated, respectively. Then elite individuals were selected to do crossover and mutation operators based on the grid domination sorting and grid selection strategies. The individuals were iterated toward the Pareto front and the Pareto optimal solutions were obtained. Finally, the proposed algorithm was verified effectively through four test functions and two practical engineering problems.