Flexible flow shop equipment utilization rate with time window constraints scheduling optimization problems

Towards to the utilization optimization problem of a flexible flow shop equipment with time window constraints, this paper proposed an information entropy-based adaptive CGA algorithm to solve the problem, and constructed the flexible flow shop production scheduling model with time window constraints. Global optimization procedure used adaptive CGA optimization algorithm, and simultaneously optimized online ordering and parallel station allocation. Time window constraints are used to control starting time of job during local optimization and the processing path and processing order of production jobs are determined through population designating distribution information and FIFO rule information to achieve the purpose of improving equipment utilization rate and production resources optimization. By comparing and analyzing the numerical results of the multi-group schemes, the improved adaptive CGA algorithm is proved effectiveness to solve the flexible flow shop equipment utilization rate optimization problem.