Research on Production Scheduling in Machining Jobshop Based on Improved Genetic Algorithm and Flexsim Simulation
In the context of carbon trading policies,conducting research on production scheduling issues in flexible job shop environments,considering the volatility of the scheduling environment in flexible job shops,the processing time of workpieces with fluctuations is represented using interval numbers.To address this issue,a mixed-integer programming model is constructed by combining interval number theory.The model aims to optimize interval completion time and interval carbon trading costs.An interval memetic algorithm(IMA)is proposed for solving the scheduling problem.To enhance the algorithm's performance,a dual-population heuristic machine selection strategy and a local search strategy based on dual-objective optimization are introduced.Finally,the effectiveness of IMA in solving the problem is validated through examples.
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维普
