Results 21 to 30 of about 4,898 (223)
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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Complexity, 2023 Swarm intelligence algorithms are metaheuristics inspired by the collective behavior of species such as birds, fish, bees, and ants. They are used in many optimization problems due to their simplicity, flexibility, and scalability.
Alam Zeb +4 more
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On deciding when to stop metaheuristics: Properties, rules and termination conditions
Operations Research Perspectives, 2023 Most metaheuristics lack a termination condition based on reasonable premises and guaranteeing the quality of the solution provided by the algorithm. We propose a methodological frame that distinguishes the concepts of properties of the final incumbent ...
Albert Corominas
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Taxonomy of Memory Usage in Swarm Intelligence-Based Metaheuristics
مجلة بغداد للعلوم, 2019 Metaheuristics under the swarm intelligence (SI) class have proven to be efficient and have become popular methods for solving different optimization problems. Based on the usage of memory, metaheuristics can be classified into algorithms with memory and
Yasear et al.
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A hyper-matheuristic approach for solving mixed integer linear optimization models in the context of data envelopment analysis [PDF]
PeerJ Computer Science, 2022 Mixed Integer Linear Programs (MILPs) are usually NP-hard mathematical programming problems, which present difficulties to obtain optimal solutions in a reasonable time for large scale models.
Martin Gonzalez +3 more
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Hybrid Metaheuristics to the Automatic Selection of Features and Members of Classifier Ensembles
Information, 2018 Metaheuristic algorithms have been applied to a wide range of global optimization problems. Basically, these techniques can be applied to problems in which a good solution must be found, providing imperfect or incomplete knowledge about the optimal ...
Antonino A. Feitosa Neto +2 more
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Multimethodology in Metaheuristics [PDF]
Journal of the Operational Research Society, 2013 As a combination of different methodologies or parts of methodologies, Multimethodology is becoming more frequent in OR practice. This paper contributes with a new proposal and a new field of application: the employment of Multimethodology in problem solving with Metaheuristics (Mh).
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Embedded Learning Approaches in the Whale Optimizer to Solve Coverage Combinatorial Problems
Mathematics, 2022 When we face real problems using computational resources, we understand that it is common to find combinatorial problems in binary domains. Moreover, we have to take into account a large number of possible candidate solutions, since these can be numerous
Marcelo Becerra-Rozas +6 more
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Towards a Generalised Metaheuristic Model for Continuous Optimisation Problems
Mathematics, 2020 Metaheuristics have become a widely used approach for solving a variety of practical problems. The literature is full of diverse metaheuristics based on outstanding ideas and with proven excellent capabilities.
Jorge M. Cruz-Duarte +5 more
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Hybrid Metaheuristics for Multi-Objective Optimization
Journal of Algorithms & Computational Technology, 2015 Over the last two decades, interest on hybrid metaheuristics has risen considerably in the field of multi-objective optimization (MOP). The best results found for many real-life or academic multi-objective optimization problems are obtained by hybrid ...
E-G. Talbi
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