Swarm Intelligent Optimization Algorithm For Disassembly Line Balancing Problem

The establishment of extended manufacturer responsibility along with new, more rigid environmental legislation and increased public awareness has caused an increasing number of manufacturers to begin recycling and remanufacturing their post-consumed products. In addition, the economic attractiveness of reusing products instead of disposing of them has further drived this effort. The first key step of product reuse, recycling, remanufacturing, storage and reasonably processing product is disassembly. Disassembly line is the best choice for automated disassembly of returned products, it is therefore of importance that it be designed and balanced to work efficiently. So research on disassembly line balancing problem has important theoretical and practical significance.Combining characteristics of disassembly line, a mathematical model was establish with optimization objectives of minimizing the number of workstations, make free time equal as far as possible, at the same time considering the hazard, demand and direction of components of returned products, then two kinds of swarm intelligent optimization algorithm, particle swarm optimization algorithm and ant colony algorithm is used to study the multi-objective remove line balance problem.A particle swarm algorithm based on objective prioritize was developed for multi-objective disassembly line balancing problem. The algorithm generated the particle’s position and speed based on random number, and the position and speed is updated by corresponding random number to add and subtract, then the random number of the position as the weight of parts is used to choose remove parts. Finally, example verification is carried out, and which indicates the validity of the proposed algorithm.A particle swarm algorithm based on pareto was developed for multi-objective disassembly line balancing problem. In this algorithm, niche technology was used to guide ant to search the global optimal solution. Pareto dominant and dispersion degree was applied to evaluate the ant and selection of local optimum solution. Finally, example verification is carried out, and which indicates the validity of the proposed algorithmAn ant colony optimization algorithm based on objective prioritize was developed for multi-objective disassembly line balancing problem. The heuristic information collaboratively considers the remove time, the harm and the demand of parts, a hybrid search mechanism by considering utilizing prior knowledge, exploring new path, random selection modes comprehensively was constructed, which improves the search efficiency of algorithm. Finally, example verification is carried out, and which indicates the validity of the proposed algorithm.