Name
Title | ||
|---|---|---|
Solving Sequence-dependent Disassembly Line Balancing Problem with Improved Cuckoo Search Algorithm |
Abstract | ||
|---|---|---|
In this paper, we describe two meta-heuristic algorithms, a discrete cuckoo search algorithm (CS) and a genetic algorithm (GA), for finding of a near optimal solution of an NP-hard combinational sequence-dependent disassembly line-balancing problem. Both algorithms use population-based evolution strategies while they have different ways in exploring a search space. GA is inspired by natural evolution concepts and the search space is explored randomly, while in CS, strategical decisions are made to explore a search space and to update the individuals in a more efficient way. A comparison between two algorithms is performed, in terms of the number of optimal solution occurrences with a number of generations, and the results clearly show that CS algorithm outperforms GA in solving the concerned problem. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/SMC.2019.8914273 | 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC) |
Keywords | Field | DocType |
Disassembly line balancing,Metaheuristic algorithms,Cuckoo Search,Genetic algorithm | Computer science,Algorithm,Cuckoo search,Line balancing | Conference |
ISSN | ISBN | Citations |
1062-922X | 978-1-7281-4570-9 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ronghe Zhou | 1 | 0 | 0.34 |
| Xiwang Guo | 2 | 4 | 4.53 |
| Yaping Fu | 3 | 14 | 2.54 |
| Liang Qi | 4 | 156 | 27.14 |