Open AccessAdjustable mode ratio and focus boost search strategy for cat swarm optimization
Author(s) -
PeiWei Tsai,
AUTHOR_ID,
Xingsi Xue,
Jing Zhang,
Vaci Istanda,
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AUTHOR_ID,
AUTHOR_ID,
AUTHOR_ID
Publication year - 2021
Publication title -
applied computing and intelligence
Language(s) - English
Resource type - Journals
ISSN - 2771-392X
DOI - 10.3934/aci.2021005
Subject(s) - differential evolution , particle swarm optimization , swarm behaviour , evolutionary algorithm , sensitivity (control systems) , mathematical optimization , ranking (information retrieval) , multi swarm optimization , computer science , mode (computer interface) , algorithm , mathematics , artificial intelligence , engineering , electronic engineering , operating system
Evolutionary algorithm is one of the optimization techniques. Cat swarm optimization (CSO)-based algorithm is frequently used in many applications for solving challenging optimization problems. In this paper, the tracing mode in CSO is modified to reduce the number of user-defined parameters and weaken the sensitivity to the parameter values. In addition, a mode ratio control scheme for switching individuals between different movement modes and a search boosting strategy are proposed. The obtained results from our method are compared with the modified CSO without the proposed strategy, the original CSO, the particle swarm optimization (PSO) and differential evolution (DE) with three commonly-used DE search schemes. Six test functions from IEEE congress on evolutionary competition (CEC) are used to evaluate the proposed methods. The overall performance is evaluated by the average ranking over all test results. The ranking result indicates that our proposed method outperforms the other methods compared.