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Template method hyper-heuristics

Proceedings of the Companion Publication of the 2014 Annual Conference on Genetic and Evolutionary Computation, 2014
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].
John Robert Woodward, Jerry Swan
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A comprehensive analysis of hyper-heuristics

Intelligent Data Analysis, 2008
Meta-heuristics such as simulated annealing, genetic algorithms and tabu search have been successfully applied to many difficult optimization problems for which no satisfactory problem specific solution exists. However, expertise is required to adopt a meta-heuristic for solving a problem in a certain domain. Hyper-heuristics introduce a novel approach
Ender Özcan   +2 more
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A hyper-heuristic clustering algorithm

2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2012
The so-called heuristics have been widely used in solving combinatorial optimization problems because they provide a simple but effective way to find an approximate solution. These technologies are very useful for users who do not need the exact solution but who care very much about the response time. For every existing heuristic algorithm has its pros
Chun-Wei Tsai   +2 more
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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   +4 more
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An investigation of hyper-heuristic search spaces

2007 IEEE Congress on Evolutionary Computation, 2007
Hyper-heuristics or "heuristics that coordinate heuristics" are fast becoming popular for solving combinatorial optimisation problems. These methods do not search directly the solution space; they do it indirectly through the exploration of the space of heuristics and/or their combinations. This space is named the associated space.
José Antonio Vázquez Rodríguez   +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 ...
Ching-Yuen Chan   +3 more
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Evolutionary Cross-Domain Hyper-Heuristics

Proceedings of the Companion Publication of the 2015 Annual Conference on Genetic and Evolutionary Computation, 2015
Designing effective algorithms to solve computational problems is difficult and time-consuming. The standard methodology for designing such algorithms is “top-down”. This process breaks down large problems into more understood components and eventually identifies problem-specific operators that algorithms need to use to solve the given problem.
Patricia Ryser-Welch   +2 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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A Hyper-Heuristic Scheduling Algorithm for Cloud

IEEE Transactions on Cloud Computing, 2014
Rule-based scheduling algorithms have been widely used on many cloud computing systems because they are simple and easy to implement. However, there is plenty of room to improve the performance of these algorithms, especially by using heuristic scheduling.
Chun-Wei Tsai   +4 more
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Introduction to Hyper-Heuristics

2018
Research into solving combinatorial optimization problems such as timetabling, vehicle routing and rostering problems has involved deriving techniques that improve the results obtained by existing techniques for known benchmark sets. These benchmark sets are made publicly available for performance comparisons of different techniques in solving these ...
Nelishia Pillay, Rong Qu
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