An improved multi-objective hybrid algorithm(MOGATS)that combines NSGA-Ⅱ and tabu search is proposed for flexible job shop scheduling problem with dual resource constraints of machines and workers.The algorithm takes into account various factors that affect processing time and aims to minimize the completion time,production cost,and total energy consumption of the workshop.The algorithm incorpo-rates a hybrid initialization method to ensure both the quality and diversity of the initial solutions.It employs a greedy decoding strategy based on considering transportation time and utilizes adaptive crossover and mu-tation operators.The algorithm identifies the optimal individuals for each objective in the Pareto front and applies tabu search.The two algorithms are integrated to enhance the global and local search capabilities.Simulation results on instances demonstrate that the MOGATS algorithm outperforms the compared algo-rithms,confirming its effectiveness and feasibility.
behavioral effectdual resourceNSGA-Ⅱtabu searchtransportation time
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