Optimization of Ship Outfitting Operation Plan Based on Improved NSGA-Ⅱ Algorithm
Aiming at the problems of low efficiency in the planning of ship outfitting operation,and the planning results do not meet the expected requirements of operation,a multi-objective optimization model of time limit,cost and resources under the condition of multi-execution mode resource restric-tion was established.An improved non-dominated sorting genetic algorithm(NSGA-Ⅱ)was pro-posed,which used random crossover operator,greedy mutation operator and adaptive evolutionary probability to improve the efficiency of population evolution.Meanwhile,the simulated annealing al-gorithm was combined to enhance the local search ability of the algorithm,and the improved algorithm was used to simulate the example.The results show that this method can carry out multi-objective op-timal control of ship outfitting operation plan and realize intelligent optimal compilation of outfitting operation plan.Through the comparative analysis of the algorithms,the feasibility and effectiveness of the improved NSGA-Ⅱ algorithm are verified.
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