It is of great significance to comprehensively enhance the sustainability of production scheduling with economic,environmental and social demand.A scheduling model for parallel machine production is established with consideration of four decision tasks:Machine assignment,processing sequence,personnel arrangement,and on/off machine control.To solve this complex problem,a dual-enhanced memetic algorithm(DMA)that integrates two local optimization strategies is proposed.In a random manner,a one-step variable neighborhood search(1S-VNS)suitable for decision-making tasks is designed.For targeted optimization,a sustainable goals-oriented strategy(SGS)is constructed after analyzing the matching relationship between objectives and key tasks.Based on the dif-ferent characteristics of the two optimization strategies,the 1S-VNS acts on the entire population,and the SGS strengthens the elite individuals,achieving dual optimization of the output solution set.The simulation experiment-al results show that the dual optimization strategies effectively enhance the algorithm performance,and the pro-posed DMA has superiority in diversity and convergence of non-dominated solutions.
维普
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