Multi-Point Simulated Annealing with Adaptive Neighborhood
Summary :
When Simulated Annealing (SA) is applied to continuous optimization problems, the design of the neighborhood used in SA becomes important. Many experiments are necessary to determine an appropriate neighborhood range in each problem, because the neighborhood range corresponds to distance in Euclidean space and is decided arbitrarily. We propose Multi-point Simulated Annealing with Adaptive Neighborhood (MSA/AN) for continuous optimization problems, which determine the appropriate neighborhood range automatically. The proposed method provides a neighborhood range from the distance and the design variables of two search points, and generates candidate solutions using a probability distribution based on this distance in the neighborhood, and selects the next solutions from them based on the energy. In addition, a new acceptance judgment is proposed for multi-point SA based on the Metropolis criterion. The proposed method shows good performance in solving typical test problems.
- Publication
- IEICE TRANSACTIONS on Information Vol.E90-D No.2 pp.457-464
- Publication Date
- 2007/02/01
- Publicized
- Online ISSN
- 1745-1361
- DOI
- 10.1093/ietisy/e90-d.2.457
- Type of Manuscript
- Special Section PAPER (Special Section on Foundations of Computer Science)
- Category
- Optimizing Algorithms
Authors
Keyword
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Keiko ANDO, Mitsunori MIKI, Tomoyuki HIROYASU, "Multi-Point Simulated Annealing with Adaptive Neighborhood" in IEICE TRANSACTIONS on Information,
vol. E90-D, no. 2, pp. 457-464, February 2007, doi: 10.1093/ietisy/e90-d.2.457.
Abstract: When Simulated Annealing (SA) is applied to continuous optimization problems, the design of the neighborhood used in SA becomes important. Many experiments are necessary to determine an appropriate neighborhood range in each problem, because the neighborhood range corresponds to distance in Euclidean space and is decided arbitrarily. We propose Multi-point Simulated Annealing with Adaptive Neighborhood (MSA/AN) for continuous optimization problems, which determine the appropriate neighborhood range automatically. The proposed method provides a neighborhood range from the distance and the design variables of two search points, and generates candidate solutions using a probability distribution based on this distance in the neighborhood, and selects the next solutions from them based on the energy. In addition, a new acceptance judgment is proposed for multi-point SA based on the Metropolis criterion. The proposed method shows good performance in solving typical test problems.
URL: https://global.ieice.org/en_transactions/information/10.1093/ietisy/e90-d.2.457/_p
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@ARTICLE{e90-d_2_457,
author={Keiko ANDO, Mitsunori MIKI, Tomoyuki HIROYASU, },
journal={IEICE TRANSACTIONS on Information},
title={Multi-Point Simulated Annealing with Adaptive Neighborhood},
year={2007},
volume={E90-D},
number={2},
pages={457-464},
abstract={When Simulated Annealing (SA) is applied to continuous optimization problems, the design of the neighborhood used in SA becomes important. Many experiments are necessary to determine an appropriate neighborhood range in each problem, because the neighborhood range corresponds to distance in Euclidean space and is decided arbitrarily. We propose Multi-point Simulated Annealing with Adaptive Neighborhood (MSA/AN) for continuous optimization problems, which determine the appropriate neighborhood range automatically. The proposed method provides a neighborhood range from the distance and the design variables of two search points, and generates candidate solutions using a probability distribution based on this distance in the neighborhood, and selects the next solutions from them based on the energy. In addition, a new acceptance judgment is proposed for multi-point SA based on the Metropolis criterion. The proposed method shows good performance in solving typical test problems.},
keywords={},
doi={10.1093/ietisy/e90-d.2.457},
ISSN={1745-1361},
month={February},}
Copy
TY - JOUR
TI - Multi-Point Simulated Annealing with Adaptive Neighborhood
T2 - IEICE TRANSACTIONS on Information
SP - 457
EP - 464
AU - Keiko ANDO
AU - Mitsunori MIKI
AU - Tomoyuki HIROYASU
PY - 2007
DO - 10.1093/ietisy/e90-d.2.457
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E90-D
IS - 2
JA - IEICE TRANSACTIONS on Information
Y1 - February 2007
AB - When Simulated Annealing (SA) is applied to continuous optimization problems, the design of the neighborhood used in SA becomes important. Many experiments are necessary to determine an appropriate neighborhood range in each problem, because the neighborhood range corresponds to distance in Euclidean space and is decided arbitrarily. We propose Multi-point Simulated Annealing with Adaptive Neighborhood (MSA/AN) for continuous optimization problems, which determine the appropriate neighborhood range automatically. The proposed method provides a neighborhood range from the distance and the design variables of two search points, and generates candidate solutions using a probability distribution based on this distance in the neighborhood, and selects the next solutions from them based on the energy. In addition, a new acceptance judgment is proposed for multi-point SA based on the Metropolis criterion. The proposed method shows good performance in solving typical test problems.
ER -
English
