Research On Dual Resource Constrained Flexible Job Shop Scheduling Problem With Energy-efficient

With the rapid development of workshop production automation and intelligent technology,how enterprises can manufacture small-batch and customized production with high efficiency,low cost,and low energy consumption to meet the diverse and individualized needs of customers has become the core competitiveness.Flexible job-shop scheduling problem(FJSP)optimization is the key technology to solve this problem.In this paper,the problems existing in the flexible job shop are studied in depth,and the chemical reaction algorithm is combined with the local search to find the best solution for arranging process sequences and allocating flexible resources so as to improve the production efficiency of the workshop.In the second chapter of this paper,a mixed integer programming model of FJSP is seted up with the goal of minimizing the maximum completion time.The chemical reaction algorithm and tabu search are used to solve the problem.In the algorithm,the full active decoding method is used to optimize the process sequence,and the quality of solution is improved while the idle time of machine is reduced.A greedy selection initialization method based on process completion time is proposed to improve the initial population.The on-wall ineffective collision in the chemical reaction is performed by a mutation operator,the decomposition is performed using a circular shift operation,the inter-molecular ineffective collision is performed by a crossover operator,and the synthesis is performed by a distance maintaining crossover operation.At the same time,tabu search is introduced into the algorithm to improve the local search ability of the algorithm.In the third chapter,based on the FJSP problem,the mathematical model of dual resource constrained flexible job-shop scheduling problem(DRCFJSP)is established by considering the worker constraints.Design a fully active decoding method,crossover operator and mutation operator for DRCFJSP.According to the characteristics of DRCFJSP,three neighborhood structures are designed and a variable neighbourhood search is applied for local search.The fourth chapter considers the energy consumption and processing cost in the workshop based on the makespan as the goal,and establishes a multi-objective optimization model for the DRCFJSP problem.In the decoding,the switch strategy and delay processing strategy are introduced to reduce the idle energy consumption of the machine tool,the multi-objective optimization theory,the chemical reaction optimization algorithm,and a multi-objective local search based on non-dominated sorting is applied.Finally,the hybrid algorithm is used to solve the classic cases and the reasonable cases designed by ourselves.The results are compared with other algorithms to verify the performance of the hybrid algorithm,and the influence of the system parameters on the performance of the algorithm is examined through the experimental design method.