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An Improved Multi-objective Multi-verse Optimization Algorithm for Multifunctional Robotic Parallel Disassembly Line Balancing Problems

Shancheng Zhang, Xiwang Guo, Jiacun Wang, Shixin Liu, Shujin Qin, Ziyan Zhao

Year
2022
Citations
6

Abstract

With the rapid development of science and technology, a large amount of electronic waste is inevitably generated from various discarded and End-Of-Life electronic products. If these products are not handled properly, they can cause environmental pollution as well as loss of resources. As an important part of remanufacturing, disassembly is usually done manually with low efficiency and high labor cost. In this paper, parallel disassembly lines with multiple robots are proposed. These robots can run automatically and be used to perform disassembly in an optimal disassembly mode. A multitype robot can be flexibly set with multiple functions. A mathematical model is established to assign disassembly tasks to the robots such that a line can achieve the maximum profit and minimum carbon emissions. An improved multi-objective multi-verse optimizer is proposed and applied to a set of instances. Experimental results show that the algorithm has an overwhelming performance advantage over the other three commonly-used algorithms in solving this problem. It has better performance than the other peer algorithms in solving parallel disassembly line balancing problems.

Keywords

RemanufacturingComputer scienceRobotProduction lineEnvironmental pollutionSet (abstract data type)Mathematical optimizationDistributed computingArtificial intelligenceManufacturing engineering

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