Results 201 to 210 of about 3,693 (219)

Evolutionary multilabel hyper-heuristic design

2017 IEEE Congress on Evolutionary Computation (CEC), 2017
Nowadays, heuristics represent a commonly used alternative to solve complex optimization problems. This, however, has given rise to the problem of choosing the most effective heuristic for a given problem. In recent years, one of the most used strategies for this task has been the hyper-heuristics, which aim at selecting/generating heuristics to solve ...
Alejandro Rosales-Perez, Andres E. Gutierrez-Rodriguez, Jose C. Ortiz-Bayliss, Hugo Terashima-Marin, Carlos A. Coello Coello   +4 more
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Generative Hyper-heuristics

Proceedings of the Companion Conference on Genetic and Evolutionary Computation, 2022
Daniel R. Tauritz, John R. Woodward
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New Insights Into Diversification of Hyper-Heuristics

IEEE Transactions on Cybernetics, 2014
There has been a growing research trend of applying hyper-heuristics for problem solving, due to their ability of balancing the intensification and the diversification with low level heuristics. Traditionally, the diversification mechanism is mostly realized by perturbing the incumbent solutions to escape from local optima. In this paper, we report our
Zhilei, Ren, He, Jiang, Jifeng, Xuan, Yan, Hu, Zhongxuan, Luo   +4 more
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HHFS: Hyper-heuristic feature selection

Intelligent Data Analysis, 2016
Feature selection is an important machine learning field which can provide a key role for the challenging problem of classifying high-dimensional data. This problem is finding effective features among the set of all features in such that the final feature set can improve accuracy and reduce complexity.
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Hyper-Heuristics with Low Level Parameter Adaptation

Evolutionary Computation, 2012
Recent years have witnessed the great success of hyper-heuristics applying to numerous real-world applications. Hyper-heuristics raise the generality of search methodologies by manipulating a set of low level heuristics (LLHs) to solve problems, and aim to automate the algorithm design process.
Zhilei, Ren, He, Jiang, Jifeng, Xuan, Zhongxuan, Luo   +3 more
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Selection hyper-heuristics

Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2022
Kheiri, Ahmed, Keedwell, Edward
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Evolutionary Algorithms and Hyper-Heuristics

2015
This chapter presents the basic concepts of evolutionary algorithms (EAs) and hyper-heuristics (HHs), which are computational techniques directly explored in this book. EAs are well-known population-based metaheuristics. They have been employed in artificial intelligence over several years with the goal of providing the near-optimal solution for a ...
Rodrigo C. Barros, André C. P. L. F. de Carvalho, Alex A. Freitas   +2 more
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A Hyper-Heuristic Inspired by Pearl Hunting

2012
Pearl hunting is a traditional way of diving to retrieve pearl from pearl oysters or to hunt some other sea creatures. In some areas, hunters need to dive and search seafloor repeatedly at several meters depth for pearl oysters. In a search perspective, pearl hunting consists of repeated diversification (to surface and change target area) and ...
Chan, CY, Xue, F, Ip, WH, Cheung, CF
openaire   +3 more sources

Hyper-heuristics for cross-domain search

Bulletin of the Polish Academy of Sciences: Technical Sciences, 2012
Abstract In this paper we present two hyper-heuristics developed for the Cross-Domain Heuristic Search Challenge. Hyper-heuristics solve hard combinatorial problems by guiding low level heuristics, rather than by manipulating problem solutions directly. Two hyper-heuristics are presented: Five Phase Approach and Genetic Hive.
T. Cichowicz, M. Drozdowski, M. Frankiewicz, G. Pawlak, F. Rytwinski, J. Wasilewski   +5 more
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Multi-Agent Election-Based Hyper-Heuristics

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018
Hyper-heuristics are high-level methodologies responsible for automatically discover how to combine elements from a low-level heuristic set in order to solve optimization problems. Agents, in turn, are autonomous component responsible for watching an environment and perform some actions according to their perceptions.
Vinicius Renan de Carvalho, Jaime Simão Sichman   +1 more
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