A Pareto Artificial Fish Swarm Algorithm For Multi-objective Bucket Brigades Disassembly Line Balancing Problem

The rapid development of science and technology speeds up the updating of the products,resulting in a large number of waste mechanical and electrical products.Operating the demolition of waste mechanical and electrical products to achieve the recycling of the waste products is not only the requirements of green manufacturing,but also eases the increasingly tense demand for resources situation,and brings huge economic benefits for the disassembly enterprises.The disassembly line is an inevitable choice to realize the large-scale and automated disassembly operations.The research of the disassembly line balancing problem gains the important theoretical research significance and wide practical application value.It is very difficult to realize the balance in the traditional production line with fixed workstation cycle time,while the bucket brigades production organization way possesses a high degree of balance.Through the theoretical analysis and simulation,it is verified that the bucket brigades system still maintains a high degree of balance when considering the return speed.And then a mathematical model of the bucket brigades disassembly line balancing problem based on the bucket brigades production organization way is established.The mathematical model includes multiple objectives which not only consider the balance characteristics of the disassembly line,but also consider disassembling the high demand and hazardous parts as soon as possible,and reduce the number of disassembly direction changes,so as to meet the disassembly line system economy,high efficiency,safety,environmental protection and other advanced manufacturing process requirements.In order to attain the equilibrium optimization of the mutually conflicting multiple objectives in the multi-objective disassembly line balancing problem,a multi-objective artificial fish swarm algorithm based on the Pareto solution set is designed which is superior to the traditional solving method in solving results diversity.The random crossover operation is used to guide the artificial fish to the optimal disassembly direction to improve the ability of artificial fish to find the better solution.The crowding distance was adopted to filter the non-inferior solutions in the prey,swarm and follow process of artificial fish to realize the diversity of each behavior solution results.By employing the strategy of elite reservation,the non-inferior solutions in the external file were added to the next iteration of the algorithm,which speeded up the convergence rate of the algorithm.An example is given to show that the proposed algorithm has excellent performance in the convergence and distribution two aspects.Then,the disassembly cases of different scale tasks are solved using the proposed algorithm and a variety of solution schemes are obtained.The validity and superiority of the proposed algorithm were verified by comparing the existing algorithms.The established model and the designed algorithm were applied to the actual disassembly line,and 16 solution schemes were acquired in solving the engine bucket brigades disassembly line balancing problem for 3 operators with the same return speed.And 20 solution schemes were obtained in solving the printer bucket brigades disassembly line balancing problem for 5 operators with the different return speed.It is identified that the balance of the disassembly production is realized,the effective disassembly operation time is improved using the proposed algorithm to solve the bucket brigades disassembly line balancing problem,and the decision makers are provided with a wide range of decision schemes.Therefore,the established model and the proposed algorithm in this paper is able to better solve the disassembly line balancing problem and effectively improve the line balancing problem,which has strong applicability and broad application prospect.