Development of a novel crossover of hybrid genetic algorithms for large-scale traveling salesman problems |
| |
Authors: | Masafumi Kuroda Kunihito Yamamori Masaharu Munetomo Moritoshi Yasunaga Ikuo Yoshihara |
| |
Affiliation: | 1. Graduate School of Engineering, University of Miyazaki, Miyazaki, Japan 2. Faculty of Engineering, University of Miyazaki, 1-1 Gakuen Kibanadai-nishi, Miyazaki, 889-2192, Japan 3. Information Initiative Center, Hokkaido University, Sapporo, Hokkaido, Japan 4. Graduate School of Systems and Information Engineering, University of Tsukuba, Tsukuba, Japan
|
| |
Abstract: | This article proposes a novel crossover operator of hybrid genetic algorithms (HGAs) with a Lin-Kernighan (LK) heuristic for
solving large-scale traveling salesman problems (TSPs). The proposed crossover, tentatively named sub-tour recombination crossover
(SRX), collects many short sub-tours from both parents under some set of rules, and reconnects them to construct a new tour
of the TSP. The method is evaluated from the viewpoint of tour quality and CPU time for ten well-known benchmarks, e.g., dj38,
qa194, …, ch71009.tsp, in the TSP website of the Georgia Institute of Technology. We compare the SRX with three conventional
crossover operators, a variant of the maximal preservative crossover operator (MPX3), a variant of the greedy sub-tour crossover
operator (GSX2), and a variant of the edge recombination crossover operator (ERX6), and show that the SRX succeeded in finding
a better solution and running faster than the conventional methods mentioned above. |
| |
Keywords: | |
本文献已被 SpringerLink 等数据库收录! |
|