求解有约束优化问题的实数遗传算法改进研究

提出一种求解有约束优化问题的改进实数遗传算法.首先,提出一种排序分组选择法,该方法具有种群多样性好、易于实现的优点.其次,给出一种基于方向的启发式交叉算子(DBHX),DBHX能够产生无数个交叉方向,且有可能产生一个引导参与交叉的染色体向最优解移动的方向vecD,即使交叉方向与vecD不一致,也有很大的可能性非常接近方向vecD,可以保证有很大的机会产生更好的子代染色体.最后,针对单一的变异算子无法兼顾局部搜索能力和全局搜索能力的缺点,提出一种组合变异方法,使得变异操作既能保证算法的局部搜索能力,又能兼顾全局搜索能力.10个实例的计算结果表明,所提出的改进实数遗传算法具有较快的收敛速度,从而验证了所提出算法的可行性和有效性.

Research on improvement of real-coded genetic algorithm for solving constrained optimization problems

An improved real-coded genetic algorithm(IRCGA) is proposed to solve constrained optimization problems. Firstly, a sorting group selection method is proposed, which has good population diversity and is easy to realize. Then, a direction-based heuristic crossover operator(DBHX) is proposed, which can generate numerous crossover directions. and it also enables a great possibility to generate a crossover direction vecD to guide the chromosomes of participation crossover to move towards the optimal solution direction. Even if the crossover direction is inconsistent with vecD, it is also very closed to the direction vecD to the utmost so as to ensure that there is a great chance to produce better offspring chromosomes. Finally, aiming at the shortcoming that a single mutation operator cannot both take into account the local search ability and the global search ability, a combined mutation method is proposed, which makes the mutation operation not only take into account the local search ability, but also the global search ability. The computing results of ten examples show that the proposed IRCGA has a fast convergence speed, and also verify its effectiveness and feasibility.