Results 31 to 40 of about 51,530 (240)
Efficiency Analysis of Swarm Intelligence and Randomization Techniques [PDF]
, 2012 Swarm intelligence has becoming a powerful technique in solving design and scheduling tasks. Metaheuristic algorithms are an integrated part of this paradigm, and particle swarm optimization is often viewed as an important landmark.
Yang, Xin-She
core +1 more source
Trigonometric words ranking model for spam message classification
IET Networks, EarlyView., 2022 Abstract The significant increase in the volume of fake (spam) messages has led to an urgent need to develop and implement a robust anti‐spam method. Several of the current anti‐spam systems depend mainly on the word order of the message in determining the spam message, which results in the system's inability to predict the correct type of message when
Suha Mohammed Hadi +7 more
wiley +1 more source
Automatic Data Clustering Using Hybrid Firefly Particle Swarm Optimization Algorithm
IEEE Access, 2019 The firefly algorithm is a nature-inspired metaheuristic optimization algorithm that has become an important tool for solving most of the toughest optimization problems in almost all areas of global optimization and engineering practices.
Moyinoluwa B. Agbaje +2 more
doaj +1 more source
On the Neutrality of Flowshop Scheduling Fitness Landscapes [PDF]
, 2011 Solving efficiently complex problems using metaheuristics, and in particular local searches, requires incorporating knowledge about the problem to solve. In this paper, the permutation flowshop problem is studied.
C.O. Wilke +15 more
core +6 more sources
IET Networks, EarlyView., 2023 We utilise a metaheuristic optimisation method, inspired by nature, called the Lévy‐flight firefly algorithm (LFA), to tackle the power regulation and user grouping in the NOMA systems. Abstract The non‐orthogonal multiple access strategies have shown promise to boost fifth generation and sixth generation wireless networks' spectral efficiency and ...
Zaid Albataineh +4 more
wiley +1 more source
Buildings, 2022 This study proposes a generally applicable improvement strategy for metaheuristic algorithms, improving the algorithm’s accuracy and local convergence in finite element (FE) model updating.
Shiqiang Qin +3 more
doaj +1 more source
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
core +1 more source
Distribution planning in a weather-dependent scenario with stochastic travel times: a simheuristics approach [PDF]
, 2018 In real-life logistics, distribution plans might be affected by weather conditions (rain, snow, and fog), since they might have a significant effect on traveling times and, therefore, on total distribution costs.
Cavero-Lázaro, Marta +4 more
core +3 more sources
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
openaire +1 more source
An Improved Bat Algorithm with Grey Wolf Optimizer for Solving Continuous Optimization Problems [PDF]
Journal of Advances in Computer Engineering and Technology, 2020 Metaheuristic algorithms are used to solve NP-hard optimization problems. These algorithms have two main components, i.e. exploration and exploitation, and try to strike a balance between exploration and exploitation to achieve the best possible near ...
narges jafari +1 more
doaj