APPLICATION OF PARTICLE SWARM OPTIMIZATION BASED ON HARMONY SEARCH STRATEGY IN SLOPE STABILITY ANALYSIS
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摘要: 土坡极限平衡稳定分析中临界滑动面的搜索是一个复杂的优化问题,在应用常规微粒群算法搜索时往往因参数较多且难以确定以及飞行速度越界的缺陷而陷入局部最优。基于对常规微粒群算法寻优思想的分析,借鉴和声算法的搜索策略来更新粒子的位置,提出基于和声策略的微粒群优化算法,该方法继承了常规微粒群算法中利用本身经验和社会认知的优势,又借鉴了和声策略的简单易行优势。将该方法应用于土坡稳定分析中,通过算例比较分析,证明新算法的有效性。Abstract: The determination of critical slip surfaces within soil slope stability analysis based on limit equilibrium method is a complicated optimization problem.However,there may exist such disadvantages as more related parameters,difficult to be determined and the possibility of exceeding the allowed ranges,when original particle swarm optimization(PSO) is used to locate the critical slip surfaces of soil slopes.The search procedure used in original PSO and the harmony search procedure are combined to generate a new position of particle in the new algorithm presented in this paper.The new algorithm takes good advantage of both PSO and HSA(harmony search algorithm),the new algorithm is applied to perform the slope stability analysis and the comparative study shows that the new algorithm is simple and can be used for slope stability analysis.
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