Home /Research /An Improved Tabu Search Algorithm for Multi-robot Hybrid Disassembly Line Balancing Problems
SWARM

An Improved Tabu Search Algorithm for Multi-robot Hybrid Disassembly Line Balancing Problems

Shiqi Zhang, Peisheng Liu, Xiwang Guo, Jiacun Wang, Shujin Qin, Ying Tang

Year
2022
Citations
4

Abstract

In recent years, the progress in the global industrialization process and the continuous advances in science and technology have brought great improvement to people's living standards. The continuous expansion of manufacturing production has produced hundreds of millions of industrial wastes. Disassembly is one of the most effective ways to recycle wastes. Traditional manual disassembly incurs high cost and cause severe safety risks. In this paper, a hybrid disassembly line balancing problem based on different types of robots is addressed by combining the different advantages of a U-shaped disassembly line and a single-row disassembly line. A mathematical model is established to maximize the recovery profit. Based on an improved tabu search algorithm, two different neighborhoods are designed and the initial feasible solutions are obtained by using a greedy algorithm. Experimental results show that the near optimal solution obtained by the algorithm is better than the initial feasible solution in a short time for large-scale examples.

Keywords

Tabu searchComputer scienceMathematical optimizationGreedy algorithmRobotAlgorithmArtificial intelligenceMathematics

Related papers

Browse all SWARM papers