基于改进龙虾算法的土石方调配优化  

Optimization of Earthwork Allocation Based on Improved Crayfish Algorithm

作　　者：胡长远 韦雪情 马仪 HU Changyuan;WEI Xueqing;MA Yi(School of Engineering,Lishui University,Lishui 323000,Zhejiang)

机构地区：[1]丽水学院工学院,浙江丽水323000

出　　处：《丽水学院学报》2024年第5期59-67,共9页Journal of Lishui University

摘　　要：针对龙虾优化算法(COA)后期全局搜索能力不足、收敛速度慢、精度低等问题,提出一种基于精英反向学习和逆不完全伽马函数的改进龙虾优化算法(ICOA)。同时针对智能优化算法较难处理等式约束的优化问题,文章对等式约束采用了降维处理的方法,并把改进龙虾优化算法用于土石方调配优化中。与线性规划法相比,该方法对土石方调配问题的约束和目标函数的解析性质没有要求,具有可以解决实际工程中非线性约束的优点。将改进后的算法应用到实际土石方工程中,并与其他算法优化结果进行了比较,结果表明本文所提算法是有效可行的。This paper proposed an improved crayfish optimization algorithm(ICOA)based on elite inverse learning and inverse incomplete gamma function to solve the problems of the crayfish optimization algorithm(COA),such as insufficient global search ability in the later stage,slow convergence speed and low precision.Meanwhile,to solve the problem that it was difficult to deal with optimization of equality constraint with intelligent optimization algorithm,the paper used a dimension reduction method for equality constraint and applied the improved crayfish optimization algorithm to the optimization of earthwork allocation.Compared with the linear programming method,the proposed method has no requirements on the constraint of earthwork allocation and the analytic properties of objective function,which has the advantage of solving nonlinear constraints in practical engineering.This paper applies the improved algorithm to the practical earthwork engineering and compares it with the optimization results of other algorithms.The results show that the proposed algorithm is effective and feasible.

关 键 词：龙虾算法 精英反向学习 等式约束 土石方调配 

分 类 号：TU323.4[建筑科学—结构工程] TU311