| 翻訳と辞書 |
| Hyper-heuristic ： ウィキペディア英語版 |
Hyper-heuristic
A hyper-heuristic is a heuristic search method that seeks to automate, often by the incorporation of machine learning techniques, the process of selecting, combining, generating or adapting several simpler heuristics (or components of such heuristics) to efficiently solve computational search problems. One of the motivations for studying hyper-heuristics is to build systems which can handle classes of problems rather than solving just one problem.〔E. K. Burke, E. Hart, G. Kendall, J. Newall, P. Ross, and S. Schulenburg, Hyper-heuristics: An emerging direction in modern search technology, Handbook of Metaheuristics (F. Glover and G. Kochenberger, eds.), Kluwer, 2003, pp. 457–474.〕〔P. Ross, Hyper-heuristics, Search Methodologies: Introductory Tutorials in Optimization and Decision Support Techniques (E. K. Burke and G. Kendall, eds.), Springer, 2005, pp. 529-556.〕〔E. Ozcan, B. Bilgin, E. E. Korkmaz, A Comprehensive Analysis of Hyper-heuristics, Intelligent Data Analysis, 12:1, pp. 3-23, 2008.〕
There might be multiple heuristics from which one can choose for solving a problem, and each heuristic has its own strength and weakness. The idea is to automatically devise algorithms by combining the strength and compensating for the weakness of known heuristics.〔E. Ozcan, B. Bilgin, E. E. Korkmaz, Hill Climbers and Mutational Heuristics in Hyperheuristics, Lecture Notes in Computer Science, Springer-Verlag, The 9th International Conference on Parallel Problem Solving From Nature, 2006, pp. 202-211.〕 In a typical hyper-heuristic framework there is a high-level methodology and a set of low-level heuristics (either constructive or perturbative heuristics). Given a problem instance, the high-level method selects which low-level heuristic should be applied at any given time, depending upon the current problem state, or search stage.〔
== Hyper-heuristics versus meta-heuristics ==
The fundamental difference between metaheuristics and hyper-heuristics is that most implementations of metaheuristics search within a search space of problem solutions, whereas hyper-heuristics always search within a search space of heuristics. Thus, when using hyper-heuristics, we are attempting to find the right method or sequence of heuristics in a given situation rather than trying to solve a problem directly. Moreover, we are searching for a generally applicable methodology rather than solving a single problem instance.
Hyper-heuristics could be regarded as "off-the-peg" methods as opposed to "made-to-measure" metaheuristics. They aim to be generic methods, which should produce solutions of acceptable quality, based on a set of easy-to-implement low-level heuristics.
抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』
■ウィキペディアで「Hyper-heuristic」の詳細全文を読む
スポンサード リンク
| 翻訳と辞書 : 翻訳のためのインターネットリソース |
Copyright(C) kotoba.ne.jp 1997-2016. All Rights Reserved.
|
|