JACIII Vol.14 No.1 pp. 21-27
doi: 10.20965/jaciii.2010.p0021


Concept of Neighborhood Degree and its Application to Switching Plural Optimization Methods in Scheduling

Fangyan Dong*, Kewei Chen**, and Kaoru Hirota*

*Department of Computational Intelligence and Systems Science, Tokyo Institute of Technology G3-49, 4259 Nagatsuta, Midori-ku, Yokohama 226-8502, Japan

**The Computing, Designing and Integration Co., Ltd. 474-5 Tsukakoshi 3, Saiwai-ku, Kawasaki, Kanagawa 212-0024, Japan

April 23, 2009
October 23, 2009
January 20, 2010
optimization, scheduling, TSP, tabu search, simulated annealing

A concept of neighborhood degree is proposed to evaluate the quality of solutions to scheduling problems such as vehicle routing, scheduling, and dispatching problems. It is possible to apply it to the optimization process of scheduling problems in order to switch between various optimization methods by considering convergence speed and solution quality. In the experiments on TSP benchmark data, two optimization methods, i.e., tabu search and simulated annealing, are switched effectively by observing the variation of the neighborhood degree. Directions for Practical applications are also mentioned.

Cite this article as:
Fangyan Dong, Kewei Chen, and Kaoru Hirota, “Concept of Neighborhood Degree and its Application to Switching Plural Optimization Methods in Scheduling,” J. Adv. Comput. Intell. Intell. Inform., Vol.14, No.1, pp. 21-27, 2010.
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Last updated on Mar. 05, 2021