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Nested Markov chain hyper-heuristic (NMHH): a hybrid hyper-heuristic framework for single-objective continuous problems [PDF]
PeerJ Computer ScienceThis article introduces a new hybrid hyper-heuristic framework that deals with single-objective continuous optimization problems. This approach employs a nested Markov chain on the base level in the search for the best-performing operators and their ...
Nándor Bándi, Noémi Gaskó
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Forecasting Renewable energy and electricity consumption using evolutionary hyperheuristic algorithm [PDF]
Scientific ReportsThis research utilizes time series models to forecast electricity generation from renewable energy sources and electricity consumption. The configuration of optimal parameters for these models typically requires optimization algorithms, but conventional ...
Yang Cao +3 more
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Comparison of Two Algorithms for Multiline Bus Dynamic Dispatching
Discrete Dynamics in Nature and Society, 2022 Dynamic bus scheduling refers to adjusting the departure time according to the latest time-varying information or adjusting bus speed in the process of operation. These control strategies can prevent bus bunching and alleviate traffic pressure. The paper
Yingxin Liu +5 more
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MatHH: A Matlab-based Hyper-Heuristic framework
SoftwareX, 2022 Hyper-Heuristics (HHs) have proven to be a valuable tool for solving complex problems, such as Combinatorial Optimization Problems (COPs). These solvers have an assorted set of models arising through extensive research from the scientific community ...
Jorge M. Cruz-Duarte +2 more
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Complexity, 2021 In this work, we focus on the problem of selecting low-level heuristics in a hyperheuristic approach with offline learning, for the solution of instances of different problem domains.
Lucero Ortiz-Aguilar +5 more
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PHH: Policy-Based Hyper-Heuristic With Reinforcement Learning
IEEE Access, 2023 Hyper-heuristics have a high level of generality and adaptability, allowing them to effectively solve a wide range of complex optimization problems.
Orachun Udomkasemsub +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 Sequence-Based Hyper-Heuristic for Traveling Thieves
Applied Sciences, 2022 A plethora of combinatorial optimization problems can be linked to real-life decision scenarios. Even nowadays, more diverse and complex problems are popping up. One of these problems is the traveling thief problem (TTP), which combines elements from the
Daniel Rodríguez +3 more
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The SOS Platform: Designing, Tuning and Statistically Benchmarking Optimisation Algorithms [PDF]
, 2020 open access articleWe present Stochastic Optimisation Software (SOS), a Java platform facilitating the algorithmic design process and the evaluation of metaheuristic optimisation algorithms.
Caraffini, Fabio, Iacca, Giovani
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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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