Adaptive Chaos Competition Culture Algorithm and Its Application in Workshop Scheduling
Aiming at the problems of low initial population diversity,low convergence effi-ciency,and easy to fall into local optimal solution of traditional culture algorithm,this paper optimizes the design and proposes an adaptive chaotic competitive culture algorithm.The al-gorithm consists of upper belief space and lower population.space composition,the popula-tion space is the optimization subject,and the belief space controls the optimization of the population space.First,the dual_population competition mechanism that divides the popula-tion in to dominant group and the disadvantaged group is introduced in the population space,and different groups adopt different evolutionary methods,which improves the convergence effciency of the algorithm;secondly,the population is divided into The dual population com-petition mechanism of the dominant group and the disadvantaged group,and different groups adopt different evolution methods,which improves the convergence efficiency of the algo-rithm.Finally,the adaptive mutation method proposed in this paper is introduced into the dual population,which avoids the confusion that the algorithm is easy to fall into the local optimal solution in the later stage.The function optimization results highlight the efficiency of the algorithm.The algorithm is applied to the flow shop scheduling problem to solve the optimization objective of minimizing the maximum make-time.The simulation results show that the algorithm has greatly improved the convergence speed and accuracy,which proves the superiority of the algorithm.
cultural algorithmchaotic cube mappingdual population competition mecha-nismadaptive mutationflow shop scheduling
万方数据
维普
