Results 11 to 20 of about 12,030 (235)
On the role of metaheuristic optimization in bioinformatics
International Transactions in Operational Research, 2022 AbstractMetaheuristic algorithms are employed to solve complex and large‐scale optimization problems in many different fields, from transportation and smart cities to finance. This paper discusses how metaheuristic algorithms are being applied to solve different optimization problems in the area of bioinformatics.
Laura Calvet +3 more
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Influence of initialization on the performance of metaheuristic optimizers [PDF]
Applied Soft Computing, 2020 All metaheuristic optimization algorithms require some initialization, and the initialization for such optimizers is usually carried out randomly. However, initialization can have some significant influence on the performance of such algorithms. This paper presents a systematic comparison of 22 different initialization methods on the convergence and ...
Qian Li 0041 +2 more
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A novel metaheuristic optimization algorithm: the monarchy metaheuristic
TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES, 2019 In this paper, we introduce a novel metaheuristic optimization algorithm named the monarchy metaheuristic (MN). Our proposed metaheuristic was inspired by the monarchy government system. Unlike many other metaheuristics, it is easy to implement and does not need a lot of parameters. This makes it applicable to a wide range of optimization problems.
Ibtissam Ahmia, Méziane Aïder
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Scholarpedia, 2011 Many real life problems are so complex in their nature that they cannot be efficiently and reliably solved within a reasonable amount of time by using traditional methods which guaranty the optimality of the solution. However, in recent years metaheuristics have proved to offer a promising approach to tackle this kind of problems.
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Chemical-Reaction-Inspired Metaheuristic for Optimization [PDF]
IEEE Transactions on Evolutionary Computation, 2010 We encounter optimization problems in our daily lives and in various research domains. Some of them are so hard that we can, at best, approximate the best solutions with (meta-) heuristic methods. However, the huge number of optimization problems and the small number of generally acknowledged methods mean that more metaheuristics are needed to fill the
Lam, AYS, Li, VOK
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MEVO: A Metamodel-Based Evolutionary Optimizer for Building Energy Optimization
Energies, 2023 A deep energy retrofit of building envelopes is a vital strategy to reduce final energy use in existing buildings towards their net-zero emissions performance.
Rafael Batres +3 more
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Dwarf Mongoose Optimization Metaheuristics for Autoregressive Exogenous Model Identification
Mathematics, 2022 Nature-inspired metaheuristic algorithms have gained great attention over the last decade due to their potential for finding optimal solutions to different optimization problems.
Khizer Mehmood +6 more
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New Evolutionary Algorithm for Optimizing Hydropower Generation Considering Multireservoir Systems
Applied Sciences, 2019 In recent decades, solving complex real-life optimization problems has attracted the full attention of researchers. Dam and reservoir operation rules are considered one of the most complicated optimization engineering problems.
Mohammad Ehteram +9 more
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Metaheuristic optimization frameworks: a survey and benchmarking [PDF]
Soft Computing, 2011 This paper performs an unprecedented comparative study of Metaheuristic optimization frameworks. As criteria for comparison a set of 271 features grouped in 30 characteristics and 6 areas has been selected. These features include the different metaheuristic techniques covered, mechanisms for solution encoding, constraint handling, neighborhood ...
José Antonio Parejo +3 more
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Havacılık ve Uzay Teknolojileri Dergisi, 2021 Nowadays, the use of metaheuristic optimization algorithms is becoming widespread because of easy applying and be able to provide requirements in the solution of high level complex optimization problems.
Kunter Sercan SEZER, Nevra BAYHAN
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