With the aggravation of environmental pollution, how to solve the problem of waste recycling is particularly important. Product disassembly is a vital part of waste recycling. Reasonable and efficient recycling can create economic benefits while protecting the environment. Therefore, disassembly lines have been established and widely used. In this paper, a human-machine collaborative disassembly line balancing problem considering maximizing economic benefits is studied. A linear mathematical model is established, and the correctness of the model is verified. An improved cuckoo search algorithm is proposed in this paper. Experimental results show that the algorithm has higher efficiency in large-scale disassembly problems while ensuring optimal solutions.
Disassembly systems play an important role in the remanufacturing processes. It has been widely used to systematically disassemble valuable and reusable parts and raw materials from wasted or end-of-life products through a series of operations. In this work, a disassembly line balancing model is established based on an AND/OR graph. It takes precedence relation, cycle time restriction, failure risk, and time uncertainty into consideration and aims to maximize the dismantling profit and minimize the energy consumption. Then, a multi-objective discrete bat optimizer based on Pareto rules is designed. A precedence preserving crossover operator, a single point mutation operator, and a 2-optimization operator are used in the search stage. To speed up the convergence, this paper proposes an elite strategy to maintain the non-dominate solutions in the external files and verify the effectiveness of the algorithm in solving the disassembly line balancing problem by comparing it with the current popular multi-objective optimization algorithm.
The progress of science and technology leads to quick replacement of products and causes a large number of abandoned products. As one of the important steps of product recycling, disassembly can maximize the utilization of resources. Considering that most of the existing disassembly lines are operated by humans, it is of great significance to consider the change of human body posture in the disassembly process. This work divides the disassembly posture into the standing posture operation and the sitting posture operation. Then, on the premise of satisfying various constraints, a mathematical model that maximizes the profit and minimizes the number of postural changes is established. A new multi-objective discrete harmony search algorithm based on Pareto is proposed. Compared with the original harmony search algorithm and multi-objective evolutionary algorithm based on decomposition, the results show that the proposed algorithm has better performance in terms of efficiency and quality.
Disassembly line plays a crucial role in the recycling of end-of-life products, which can effectively reduce the pressure of resource shortage. Considering the development of intelligent plant, this paper studies the human-robot collaborative disassembly line balancing problem with the optimization objectives of maximizing total profit and minimizing energy consumption. The disassembly process is specified with the AND/OR graph model. In addition, a Pareto improved multiobjective shuffled frog leading algorithm is proposed, which introduces an elitist strategy to improve the searching ability. Finally, the proposed model and algorithm are applied to instances of human-robot collaborative disassembly lines. Through different comparison experiments with the nondominated sorting genetic algorithm II and harmony search, the superiority of the proposed algorithm in performance and quality is verified.
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