By borrowing the ideas of population from genetic algorithms, we introduce an adaptive random search in quasi_Monte Carlo method (AQMC) for global optimization.
借用遗传算法中种群的概念，介绍了一种解全局优化的拟蒙特卡罗自适应搜索算法。
Particle swarm optimization is a kind of self-adaptive random algorithm based on group hunting strategy.
粒子群优化算法是一种基于种群搜索策略的自适应随机算法。
The experiment result shows that problems of local optimization and premature constringency were resolved with the original group in GA adaptive random search.
试验结果表明，初始种群克服了GA自适应随机搜索局部最优和过早收敛问题。
The experiment result shows that problems of local optimization and premature constringency were resolved with the original group in GA adaptive random search.
试验结果表明，初始种群克服了GA自适应随机搜索局部最优和过早收敛问题。
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