Template method hyper-heuristics
Template method hyper-heuristics
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DOI：
10.1145/2598394.2609843
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发表时间：
2014-07
期刊：
影响因子：
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通讯作者：
J. Woodward;J. Swan
中科院分区：
文献类型：
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作者：
J. Woodward;J. Swan
优化文献充斥着隐喻启发的元启发式学及其随后的变体和杂交。这导致了大量方法，其中的描述通常被隐喻的语言污染，这启发了它们[8]。在如此零散的领域中，手动“操作员调整”的传统方法使得很难确定单个元启发式组件对方法论的整体成功的贡献。不管它是否碰到最好的最先进的情况，这种“调整”都是如此强大的劳动力，因此对提高科学理解的影响很少。因此，为了引入进一步的结构和严格性，因此不仅可以指定整个元启发式学家族（而不是单个元启发式学），而且还可以产生和测试它们。特别是，采用不可知论的方法来产生元硫疗法，将有助于确定哪些元启发式成分是解决方案的有用贡献者。
The optimization literature is awash with metaphorically-inspired metaheuristics and their subsequent variants and hybridizations. This results in a plethora of methods, with descriptions that are often polluted with the language of the metaphor which inspired them [8]. Within such a fragmented field, the traditional approach of manual 'operator tweaking' makes it difficult to establish the contribution of individual metaheuristic components to the overall success of a methodology. Irrespective of whether it happens to best the state-of-the-art, such 'tweaking' is so labour-intensive that does relatively little to advance scientific understanding. In order to introduce further structure and rigour, it is therefore desirable to not only to be able to specify entire families of metaheuristics (rather than individual metaheuristics), but also be able to generate and test them. In particular, the adoption of a model agnostic approach towards the generation of metaheuristics would help to establish which metaheuristic components are useful contributors to a solution.