Results 41 to 50 of about 1,200,755 (251)
Dynamic heuristic set selection for cross-domain selection hyper-heuristics [PDF]
, 2021 Selection hyper-heuristics have proven to be effective in solving various real-world problems. Hyper-heuristics differ from traditional heuristic approaches in that they explore a heuristic space rather than a solution space.
Pillay, Nelishia, Hassan, Ahmed
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A Methodology for Classifying Search Operators as Intensification or Diversification Heuristics
Complexity, 2020 Selection hyper-heuristics are generic search tools that dynamically choose, from a given pool, the most promising operator (low-level heuristic) to apply at each iteration of the search process. The performance of these methods depends on the quality of
Jorge A. Soria-Alcaraz +5 more
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The automatic design of hyper-heuristic framework with gene expression programming for combinatorial optimization problems [PDF]
, 2014 Hyper-heuristic approaches aim to automate heuristic design in order to solve multiple problems instead of designing tailor-made methodologies for individual problems.
Kendall, Graham +4 more
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A greedy hyper-heuristic in dynamic environments [PDF]
Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers, 2009 If an optimisation algorithm performs a search in an environment that changes over time, it should be able to follow these changes and adapt itself for handling them in order to achieve good results. Different types of dynamics in a changing environment require the use of different approaches.
Ender Özcan +2 more
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An Ant Colony based Hyper-Heuristic Approach for the Set Covering Problem
Advances in Distributed Computing and Artificial Intelligence Journal, 2015 The Set Covering Problem (SCP) is a NP-hard combinatorial optimization problem that is challenging for meta-heuristic algorithms. In the optimization literature, several approaches using meta-heuristics have been developed to tackle the SCP and the ...
Alexandre Silvestre FERREIRA +2 more
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Hyper-Heuristic Based on ACO and Local Search for Dynamic Optimization Problems
Algorithms, 2021 Hyper-heuristics comprise a set of approaches that are motivated (at least in part) by the objective of intelligently combining heuristic methods to solve hard optimization problems.
Felipe Martins Müller +1 more
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How Much Is Too Much? Facing Practical Limitations in Hyper-Heuristic Design for Packing Problems
AlgorithmsHyper-heuristics, or simply heuristics to choose heuristics, represent a powerful approach to tackling complex optimization problems. These methods decide which heuristic to apply throughout the solving process, aiming to improve the solving process ...
José Carlos Ortiz-Bayliss +2 more
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Sequence-Based Selection Hyper-Heuristic Model via MAP-Elites
IEEE Access, 2021 Although the number of solutions in combinatorial optimization problems (COPs) is finite, some problems grow exponentially and render exact approaches unfeasible. So, approximate methods, such as heuristics, are customary.
Melissa Sanchez +3 more
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Intelligent System Design Using Hyper-Heuristics
South African Computer Journal, 2015 Determining the most appropriate search method or artificial intelligence technique to solve a problem is not always evident and usually requires implementation of the different approaches to ascertain this. In some instances a single approach may not be
Nelishia Pillay
doaj +1 more source