A Parallel Firefly Algorithm Combined with Genetic Operator and Its Application on Shop Scheduling
A parallel firefly algorithm combined with genetic operator is proposed,which is based on the idea of firefly flicker-ing and moving,and synchronizes parallel iterative solutions for two populations to improve the solving speed and quality of the algo-rithm.A multi-scale cooperative mutation operator is introduced in one of the populations,and the adaptive Gaussian variation mechanism with different variances is used to promote the entire population to explore the solution space in detail at as dispersed variation scales as possible,so that the entire population can undergo effective variation.The function optimization results show the effectiveness of the algorithm,this algorithm is used to solve flow shop scheduling problems with minimizing the maximum comple-tion time as the optimization objective,the experimental results show that compared with the traditional single algorithm,the paral-lel firefly algorithm combined with genetic operators has better performance in solving the shop scheduling problem.
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