Results 51 to 60 of about 57,703 (300)
Sensor networks security based on sensitive robots agents. A conceptual model
, 2012 Multi-agent systems are currently applied to solve complex problems. The security of networks is an eloquent example of a complex and difficult problem. A new model-concept Hybrid Sensitive Robot Metaheuristic for Intrusion Detection is introduced in the
B. Kim +11 more
core +1 more source
A simheuristic algorithm for solving an integrated resource allocation and scheduling problem [PDF]
, 2019 Modern companies have to face challenging configuration issues in their manufacturing chains. One of these challenges is related to the integrated allocation and scheduling of resources such as machines, workers, energy, etc.
Ferone, Daniele +4 more
core +1 more source
Advanced Electronic Materials, EarlyView.Ising machines are emerging as specialized hardware solvers for computationally hard optimization problems. This review examines five major platforms—digital CMOS, analog CMOS, emerging devices, coherent optics, and quantum systems—highlighting physics‐rooted advantages and shared bottlenecks in scalability and connectivity.
Hyunjun Lee, Joon Pyo Kim, Sanghyeon Kim
wiley +1 more source
A study on gender detection using multiple classifiers on voice data
Alexandria Engineering JournalResearchers have frequently used metaheuristic algorithms for various problems due to their success. In data mining studies, feature selection (FS) is an essential preprocessing step for large-scale problems.
Gülnur Yildizdan, Emine Baş
doaj +1 more source
Short-Term Hydro-Thermal-Solar Scheduling with CCGT Based on Self-Adaptive Genetic Algorithm
Energies, 2022 This paper presents a new metaheuristic approach based on a self-adaptive genetic algorithm (SAGA) for solving the short-term hydro-thermal-solar scheduling with combined-cycle (CCGT) units. First of all, the proposed approach is applied to a test system
Borche Postolov +3 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
Advanced Intelligent Discovery, EarlyView.A machine learning‐guided self‐driving laboratory screened over 500 nickel‐based layered double‐hydroxide catalysts for alkaline oxygen evolution. Out of the eight metals, the robot uncovered a quaternary Ni–Fe–Cr–Co catalysts requiring only 231 mV overpotential to reach 20 mA cm−2.
Nis Fisker‐Bødker +3 more
wiley +1 more source
MathematicsThe primary objective of introducing metaheuristic algorithms into traditional systematic logic is to minimize the cost function. However, there is a lack of research on the impact of introducing metaheuristic algorithms on the cost function under ...
Ju Chen +7 more
doaj +1 more source
A comparison of general-purpose optimization algorithms forfinding optimal approximate experimental designs [PDF]
, 2019 Several common general purpose optimization algorithms are compared for findingA- and D-optimal designs for different types of statistical models of varying complexity,including high dimensional models with five and more factors.
Garcia-Garcia, Jose Carlos +4 more
core
A New Cooperative Framework for Parallel Trajectory-Based Metaheuristics
, 2018 In this paper, we propose the Parallel Elite Biased framework (PEB framework) for parallel trajectory-based metaheuristics. In the PEB framework, multiple search processes are executed concurrently.
Shi, Jialong, Zhang, Qingfu
core +1 more source