Surrogate Ensemble-Assisted Hyper-Heuristic Algorithm for Expensive Optimization Problems
International Journal of Computational Intelligence Systems, 2023 This paper proposes a novel surrogate ensemble-assisted hyper-heuristic algorithm (SEA-HHA) to solve expensive optimization problems (EOPs). A representative HHA consists of two parts: the low-level and the high-level components.
Rui Zhong +3 more
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A hyper-heuristic based reinforcement-learning algorithm to train feedforward neural networks
Engineering Science and Technology, an International Journal, 2022 Artificial Neural Networks (ANNs) offer unique opportunities in numerous research fields. Due to their remarkable generalization capabilities, they have grabbed attention in solving challenging problems such as classification, function approximation ...
Fehmi Burcin Ozsoydan, İlker Gölcük
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A Component Based Heuristic Search Method with Evolutionary Eliminations [PDF]
, 2008 Nurse rostering is a complex scheduling problem that affects hospital personnel on a daily basis all over the world. This paper presents a new component-based approach with evolutionary eliminations, for a nurse scheduling problem arising at a major UK ...
Ahuja R. K. +23 more
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A New Hyper-Heuristic Multi-Objective Optimisation Approach Based on MOEA/D Framework
Biomimetics, 2023 A multi-objective evolutionary algorithm based on decomposition (MOEA/D) serves as a robust framework for addressing multi-objective optimization problems (MOPs).
Jiayi Han, Shinya Watanabe
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On Neighborhood Tree Search [PDF]
, 2012 We consider the neighborhood tree induced by alternating the use of different neighborhood structures within a local search descent. We investigate the issue of designing a search strategy operating at the neighborhood tree level by exploring different ...
Derbel, Bilel, Derbel, Houda
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A Novel Cooperative Multi-Stage Hyper-Heuristic for Combination Optimization Problems
Complex System Modeling and Simulation, 2021 A hyper-heuristic algorithm is a general solution framework that adaptively selects the optimizer to address complex problems. A classical hyper-heuristic framework consists of two levels, including the high-level heuristic and a set of low-level ...
Fuqing Zhao +4 more
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Optimizing the DFCN Broadcast Protocol with a Parallel Cooperative Strategy of Multi-Objective Evolutionary Algorithms [PDF]
, 2009 Proceeding of: 5th International Conference, EMO 2009, Nantes, France, April 7-10, 2009This work presents the application of a parallel coopera- tive optimization approach to the broadcast operation in mobile ad-hoc networks (manets). The optimization of
A.J. Nebro +26 more
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A Classification of Hyper-heuristic Approaches [PDF]
, 2009 The current state of the art in hyper-heuristic research comprises a set of approaches that share the common goal of automating the design and adaptation of heuristic methods to solve hard computational search problems.
A.S. Fukunaga +29 more
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Hybrid Variable Neighborhood HyperHeuristics for Exam Timetabling Problems [PDF]
, 2005 This paper presents our work on analysing the high level search within a graph based hyperheuristic. The graph based hyperheuristic solves the problem at a higher level by searching through permutations of graph heuristics rather than the actual ...
Burke, Edmund, Qu, Rong
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CUSTOMHyS: Customising Optimisation Metaheuristics via Hyper-heuristic Search
SoftwareX, 2020 There is a colourful palette of metaheuristics for solving continuous optimisation problems in the literature. Unfortunately, it is not easy to pick a suitable one for a specific practical scenario. Moreover, oftentimes the selected metaheuristic must be
Jorge M. Cruz-Duarte +4 more
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