Results 41 to 50 of about 7,687 (217)
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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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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A comparison of crossover control mechanisms within single-point selection hyper-heuristics using HyFlex [PDF]
, 2015 Hyper-heuristics are search methodologies which operate at a higher level of abstraction than traditional search and optimisation techniques. Rather than operating on a search space of solutions directly, a hyper-heuristic searches a space of low-level ...
Burke, Edmund K. +2 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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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
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IEEE AccessRobotic Mobile Fulfillment Systems (RMFS) are an example of warehouse automation. Nonetheless, the complexity of RMFS is such that tackling the entire problem at once is unfeasible. So, this work focuses on a component known as the Pod Allocation Problem
Maria Torcoroma Benavides-Robles +3 more
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HyperDE: An Adaptive Hyper-Heuristic for Global Optimization
Algorithms, 2023 In this paper, a novel global optimization approach in the form of an adaptive hyper-heuristic, namely HyperDE, is proposed. As the naming suggests, the method is based on the Differential Evolution (DE) heuristic, which is a well-established ...
Alexandru-Razvan Manescu +1 more
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Batched Mode Hyper-heuristics [PDF]
, 2013 A primary role for hyper-heuristics is to control search processes based on moves generated by neighbourhood operators. Studies have shown that such hyper-heuristics can be effectively used, without modification, for solving unseen problem instances not only from a particular domain, but also on different problem domains.
Shahriar Asta +2 more
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The Scientific Landscape of Hyper-Heuristics: A Bibliometric Analysis Based on Scopus
AlgorithmsHyper-heuristics emerged as a broader metaheuristic framework to address the limitations of traditional optimization heuristics. By abstracting the design of low-level heuristics, hyper-heuristics offer a flexible and adaptable approach to solving ...
Helen C. Peñate-Rodríguez +3 more
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Hyper-heuristic decision tree induction [PDF]
2009 World Congress on Nature & Biologically Inspired Computing (NaBIC), 2009 Hyper-heuristics are increasingly used in function and combinatorial optimization. Rather than attempt to solve a problem using a fixed heuristic, a hyper-heuristic approach attempts to find a combination of heuristics that solve a problem (and in turn may be directly suitable for a class of problem instances).
Alan Vella, David Corne, Chris Murphy
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