Hyper-heuristics: a survey of the state of the art
Hyper-heuristics: a survey of the state of the art
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DOI：
10.1057/jors.2013.71
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发表时间：
2013-12-01
影响因子：
3.6
通讯作者：
Qu, Rong
中科院分区：
文献类型：
--
作者：
Burke, Edmund K.;Gendreau, Michel;Qu, Rong
超启发式搜索包括一组方法，这些方法的动机（至少部分）是为了自动设计启发式方法来解决计算搜索问题。一个潜在的战略研究挑战是开发更普遍适用的搜索方法。超启发式是一个相对较新的术语，它在2000年首次被用来描述组合优化中的选择算法。然而，自动化物流设计的想法并不新鲜;它可以追溯到20世纪60年代。超算法的定义最近已经扩展到指一种搜索方法或学习机制，用于选择或生成算法来解决计算搜索问题。可以考虑两个主要的超启发式类别：启发式选择和启发式生成。超启发式算法的显着特征是它们在启发式算法（或启发式组件）的搜索空间上操作，而不是直接在正在解决的潜在问题的解决方案的搜索空间上操作。本文提出了一个批判性的讨论的科学文献的hyper-probabilistics，包括其起源和知识根源，详细说明的主要类型的方法，并概述了一些相关领域。最后对当前的研究趋势和未来的研究方向进行了讨论。
Hyper-heuristics comprise a set of approaches that are motivated (at least in part) by the goal of automating the design of heuristic methods to solve hard computational search problems. An underlying strategic research challenge is to develop more generally applicable search methodologies. The term hyperheuristic is relatively new; it was first used in 2000 to describe heuristics to choose heuristics in the context of combinatorial optimisation. However, the idea of automating the design of heuristics is not new; it can be traced back to the 1960s. The definition of hyper-heuristics has been recently extended to refer to a search method or learning mechanism for selecting or generating heuristics to solve computational search problems. Two main hyper-heuristic categories can be considered: heuristic selection and heuristic generation. The distinguishing feature of hyper-heuristics is that they operate on a search space of heuristics (or heuristic components) rather than directly on the search space of solutions to the underlying problem that is being addressed. This paper presents a critical discussion of the scientific literature on hyper-heuristics including their origin and intellectual roots, a detailed account of the main types of approaches, and an overview of some related areas. Current research trends and directions for future research are also discussed.