【摘要】 一般粗粒度并行遗传算法(CGGA)的性能受诸多因素的影响表现不尽如人意。以降低通信代价为主要目标,受物种金字塔模型的启发,设计了一种双阈值限制下的自调整堆结构,并对其堆调整具体操作进行了改进,以期望改进后算法中种群间的通信代价大幅度降低,优化收敛速度,提高算法效率。通过对遗传算法的几个典型测试函数通信量的分析和实验表明,基于该模型的并行遗传算法在降低通信代价、提高收敛速度、优化最终解方面收效明显。更多还原

【Abstract】 Common coarse-grained genetic algorithm(CGGA) has been criticized for many reasons.In this paper,focus on communication costs,gain the idea from creature specices pyramid structure and suggest a heap model limited under two valves expect to significantly reduce the communication costs between two groups.The expectation of migration costs and experiment on typical GA test functions in the last part of this essay all verify that this model could greatly decrease the cost of communication and accelerate the convergence speed.更多还原