Integrated Optimization Of Shop Scheduling And Equipment Maintenance Based On Hybrid TLBO Algorithm

Flexible job shop scheduling problem widely exists in practical production system. Reasonable scheduling can effectively improve the production efficiency of the workshop, shorten the manufacturing cycle, reduce the total cost of production. However, the enlistment age of workshop equipment is seen as infinity in the research on FJSP, that is the equipment is always available without considering the maintenance and repair of the equipment.Preventive maintenance(PM) is a technique which is necessary to ensure the production efficiency, reduce failure risks of major equipments. In order to ensure the smooth implementation of production plan, comprehensively considering the significant impact of equipment preventive maintenance on the production cycle and production tasks, implementing scientific and effective strategy is particularly necessary for production scheduling. So in this paper, preventive maintenance of equipment and flexible job shop scheduling are effectively integrated for optimization.Firstly, for the flexible job shop scheduling problem with a single object, an integrated optimization model of flexible job shop scheduling and preventive maintenance with a single object of minimizing the makespan is established, assuming that each machine in the process of scheduling has a fixed one or more maintenance time window, and all the machines ought to carry out the preventive maintenance in the time window. Simulated Annealing algorithm is mixed in the simple teaching-learning-based optimization, obtaining a hybrid algorithm, to improve the ability of local search for the solutions in the hybrid algorithm, making the whole algorithm have the capability of jumping out of local optimum. What's more, the structure of neighborhood is designed to improve the solution quality. The procedure and details of initialization, encoding, decoding as well as the methods of "teaching" and "learning" are designed. Last but not least, by testing several benchmark examples and particular cases, and comparing with other algorithms, the outcome demonstrates the superiority of the hybrid TLBO algorithm to solve this integrated optimization model.Secondly, according to the actual manufacturing environment of workshop, the model of the integration of PM and FJSP for optimization is established, which aims to minimize the maximum completion time, total workload of all the machines and average total cost in the scheduling process. Then a multi-objective TLBO algorithm is proposed to solving the above model, designing the corresponding coding, decoding and optimization process of the proposed algorithm. And by using the improved weighted TOPSIS method, the satisfactory solution is obtained from the Pareto solution set, in order to achieve the goals of improving equipment reliability, delivery schedule and cost saving. Finally, an case is given to validate the feasibility and effectiveness of the proposed strategy. At last, research on the integration of the flexible job shop scheduling and PM based on the reliability constraints is carried on. According to the change of the reliability of the machine in the process of scheduling, PM is dynamically arranged to ensure the reliability of the whole workload and reduce the failure rate. A multi-objective model which integrates these factors is established with three objective of minimizing the makespan, the production energy cost and the average maintenance energy cost of the equipment. An approach of advance-postpone balancing method is used to deal with the conflict between PM and the production steps, minimizing the average cost of PM as much as possible. According to the model, some instances that are corresponding to it are generated for test, and the Gantt chart of one of the results is draw to demonstrate the outcome.