| Advances in science and technology shorten the life cycle of products,resulting in a large number of waste mechanical and electrical products with renewable resources and environmental pollution.Disassembly is an important link to achieve the recycling and reuse of these products and sustainable development.In order to promote the industrialization and scale of product remanufacturing,the construction of high flexible disassembly line is an inevitable guarantee to realize efficient and batch apart.Research on disassembly line balance problems is the key to rationally planning disassembly plans and improving the efficiency of disassembly operations.Because of the complexity of disassembly operation environment,a new precedence relation matrix is proposed based on the description of AND/OR precedence relation constraint.In order to solve the problems of resources,energy consumption,balance and economic cost of actual disassembly line,comprehensively considering resource constraints,repulsive constraints,compatible constraints and other constraints,and a multi-objective disassembly line mathematical model is established to minimize the number of workstations,balance index,disassembly energy consumption,number of resources and disassembly cost.Aiming at the above multi-objective optimization model,a multi-objective discrete fruit fly optimization algorithm incorporating Pareto's idea is designed to avoid the deficiency of traditional solving methods that could not optimize multi-conflict objectives,combining the characteristics of disassembly line balance problem and Pareto's dominant idea.The algorithm adopts the coding form based on the task real number and generates the initial population by the randomization method.In order to increase the diversity of solutions,two-point mutation is used to perform olfactory search.In order to solve the problem of non-dominant ordering of individual renewal,the neighborhood solution with the largest difference is used to replace the parent to perform the visual operation.In order to increase the global optimization ability of the algorithm,a four-point crossover operation is adopted to implement the global cooperation mechanism.In order to improve the convergence effect,the elite retention strategy is adopted to maintain the non-inferior solutions in the external files.Taguchi experiment and statistical analysis method are used to determine the optimal parameter combination of the algorithm,and the results of the proposed algorithm and the existing algorithm on test cases are compared.In order to overcome the limitation of the traditional random example,a new random example rule is proposed,and the proposed algorithm is compared with the exact solution result to verify the feasibility of the random example and further prove the solution performance of the proposed algorithm.Based on the above theoretical results,the proposed algorithm and model are applied to solve the automobile disassembly example and 12 non-inferior solutions are obtained.The simulation technology is used to simulate the disassembly amount of each solution,and combining the values of the non-inferior solutions and disassembly amount as a comprehensive evaluation of decision matrix.A comprehensive evaluation model combining analytic hierarchy process(AHP)and technique for order preference by simliarity to ideal solution(TOPSIS)is used to select the best disassembly scheme and simulate it to find out the bottleneck station and improvement point,by increasing buffer and adjusting operation time,re-simulation found that the output increased by 4.53%,and the average utilization rate of equipment working status increased to 72.82%.It can be seen from this that this paper adopts the technical means of algorithm optimization,simulation analysis and multi-criteria decision-making to make a reasonable planning and balanced design for the disassembly line.By combining theory with practice,it can be closer to the actual disassembly production,which has strong theoretical and application value. |
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