Application of a Parallel Adaptive Cuckoo Search Algorithm in the Rectangle Layout Problem  

作　　者：Weimin Zheng Mingchao Si Xiao Sui Shuchuan Chu Jengshyang Pan 

机构地区：[1]College of Computer Science and Engineering,Shandong University of Science and Technology,Qingdao,266590,China

出　　处：《Computer Modeling in Engineering & Sciences》2023年第6期2173-2196,共24页工程与科学中的计算机建模（英文）

基　　金：funded by the NationalKey Research and Development Program of China under Grant No.11974373.

摘　　要：The meta-heuristic algorithm is a global probabilistic search algorithm for the iterative solution.It has good performance in global optimization fields such as maximization.In this paper,a new adaptive parameter strategy and a parallel communication strategy are proposed to further improve the Cuckoo Search(CS)algorithm.This strategy greatly improves the convergence speed and accuracy of the algorithm and strengthens the algorithm’s ability to jump out of the local optimal.This paper compares the optimization performance of Parallel Adaptive Cuckoo Search(PACS)with CS,Parallel Cuckoo Search(PCS),Particle Swarm Optimization(PSO),Sine Cosine Algorithm(SCA),Grey Wolf Optimizer(GWO),Whale Optimization Algorithm(WOA),Differential Evolution(DE)and Artificial Bee Colony(ABC)algorithms by using the CEC-2013 test function.The results show that PACS algorithmoutperforms other algorithms in 20 of 28 test functions.Due to the superior performance of PACS algorithm,this paper uses it to solve the problem of the rectangular layout.Experimental results show that this scheme has a significant effect,and the material utilization rate is improved from89.5%to 97.8%after optimization.

关 键 词：Rectangular layout cuckoo search algorithm parallel communication strategy adaptive parameter 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]