Optimization And Simulation Method Of Partial Disassembly Line Balancing Problem For Multi-Objective Discrete Cuckoo Search Algorithm

The problem of resource shortage and environmental pollution is the two challenge in the process of modern industrial development.And the large scale of waste electromechanical products have caused pressure to the environment,and at the same time,a lot of useful parts and materials are left unused,so it is necessary to recycle and reuse them.Disassembly is an important step of the green manufacturing of end of life product,and disassembly line is the best organization way for large-scale automated and efficient disassembly.The study of the disassembly line balance,aiming at the improvement of the disassembly efficiency,is of great significance to improve the degree of resource utilization and reduce the pollution of the environment.According to the disassembly degree of waste electromechanical products,the disassembly line can be divided into complete disassembly and partial disassembly.In the complete disassembly model,based on the traditional concept of disassembly line balance problem model,a disassembly line balance decomposition model was established based on the four optimization objectives to solve the disassembly task allocation problem and sequencing problem respectively.However,disassembly companies pay more attention to the dismantlement of demand parts and hazardous parts.Considering the partial disassembly of waste electromechanical products to reduce the disassembly process,thus the model of the partial disassembly line balancing that is more in line with actual production is built.In addition,due to the randomness of the disassembly operations affected by various uncertainties,in order to establish a disassembly line with both balance and flexibility,deterministic and stochastic partial disassembly line balance model are constructed respectively.In order to effectively solve the above three multi-objective disassembly line balancing problem models,a multi-objective discrete cuckoo algorithm is designed based on the Pareto dominant multi-objective processing method.The algorithm uses a task-based coding method to determine the mapping relationship between the problem model and the cuckoo bird nest position and bird egg attributes;by combining Levy flight's random step length with the weight of the disassembly task,the Levy flight operation is discretized.By using random probability to simulate the probability that the nest bird discovers the exotic bird eggs,the task with the higher probability of discovery is randomly inserted into the disassembly sequence to realize the nest parasitic operation;in order to improve the optimization ability of each single objective and to coordinate the multiple objectives,a driving operation with the single objective optimal solution as the driving solution is proposed.Through the tests of three instance problems and 19 benchmark cases,the algorithm parameters of different scale problems and the population updating strategy of heuristic rules are determined.And the effectiveness and superiority of the algorithm is verified by comparing the results of existing algorithms.Aiming at the disassembly line of the waste television,the constructed three models and the proposed algorithm are used to determine various disassembly schemes.Decision makers can choose according to different preferences.In order to establish a more practical disassembly line,it is necessary to consider the effect of the randomness of operation time on the disassembly line of continuous production.Therefore,a disassembly line design method combining the optimization of the algorithm and the simulation model is proposed,and the disassembly scheme is analyzed by the four optimization objectives and the disassembly output were compared with the results obtained by using the algorithm alone,which illustrate the effectiveness and practicality of the method.