A Novel Hybrid Sine-Cosine and Sooty Tern Optimization Algorithm Based on Chaotic Crazy Adaptation and its Engineering Application
Main girder optimization of bridge crane is a nonlinear complex constrained optimization problem.The existing meth-ods have some problems,such as slow convergence,poor stability and low convergence precision.In order to overcome this problem,a novel hybrid sine cosine and sooty tern optimization algorithm based on chaotic crazy adaptation(CCASSTOA)is proposed.Ini-tially,Logistics chaos map was introduced to initialize the population of STOA algorithm to increase the diversity of population individuals and the convergence rate in the initial iteration period.And then a hybrid search strategy of inertia adaptive weight and sine cosine algorithm(SCA)is introduced into the location update formula of sooty tern,which enhanced the balance ability between global search and local search.The optimal position of sooty tern is mutated by the crazy operator to enhance the diversity of the population in the later iteration period and avoid falling into the local optimum.Six test functions are used to verify the per-formance of the CCASSTOA algorithm.The results show that the CCASSTOA algorithm is superior to the other five meta-heuris-tic optimization algorithms with high convergence precision,good stability and strong robustness.By applying CCASSTOA algo-rithm to the lightweight design of main girder of 32t/22.5m bridge crane,the cross-section area of main girder can be reduced by about31.45%.Therefore,the CCASSTOAalgorithm can effectively deal with such nonlinear constrained optimization problems.
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