Improved COOT Algorithm to Solve Multi-Objective Flexible Jobshop Scheduling Problem

Aiming at the multi-objective flexible jobshop scheduling problem(FJSP), a model with the completion time, total machine load and energy consumption as the optimization objectives is established, and the multi-objective COOT algorithm combined with simulated annealing (MOCOOT-SA) is proposed to solve it. The algorithm optimizes the original single-objective COOT algorithm into a multi-objective algorithm by introducing the concept of archive set and Pareto solution, and selects a new neighborhood structure and update method for specific individuals, and then integrates the simulated annealing algorithm(SA)to optimize local search ability and convergence speed. Finally, the appropriate codec method is selected, the MOCOOT-SA algorithm is used to test the improved benchmark example, and compared with the results of the NSGA-II algorithm and the MOPSO algorithm, the average optimization ratio of each target is 0.013~0.047, the optimal value optimization ratio is 0.016~0.045. The results show the advantage of this algorithm that it can better solve the multi-objective FJSP. © The Author(s) 2023.