Results 21 to 30 of about 17,999 (266)
Cost-Aware and Energy-Efficient Task Scheduling Based on Grey Wolf Optimizer [PDF]
Journal of Mahani Mathematical Research, 2023 One of the principal challenges in the cloud is the task scheduling problem. Appropriate task scheduling algorithms are needed to achieve goals such as load balancing, minimum cost, minimum energy consumption, etc.
Reyhane Ghafari, Najme Mansouri
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IEEE Access, 2020 Feature Selection (FS) is an important pre-processing step in the fields of machine learning and data mining, which has a major impact on the performance of the corresponding learning models.
Shameem Ahmed +4 more
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Meta heuristics for the orienteering problem
Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600), 2003 This paper presents two meta-heuristic techniques, ant colony optimization and tabu search, for the orienteering problem, a general version of the well-known traveling salesman problem with many relevant applications in industry. Both algorithms are compared to other heuristics in the literature.
Yun-Chia Liang +2 more
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A new index‐based hyper‐heuristic algorithm for global optimisation problems
IET Software, 2022 In this research study, a new combination search algorithm, based on indexing its constituent processes, is proposed to solve global optimisation problems.
Mohammad Reza Hasanzadeh +2 more
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Accurate Solar Cell Modeling via Genetic Neural Network-Based Meta-Heuristic Algorithms
Frontiers in Energy Research, 2021 Accurate solar cell modeling is essential for reliable performance evaluation and prediction, real-time control, and maximum power harvest of photovoltaic (PV) systems.
Long Wang +7 more
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Ain Shams Engineering Journal, 2020 The growth of demand, the need for economic efficiency and optimal utilisation of electric power networks and the high cost of construction of new power networks result in inevitable challenges, such as overloading and excessive power transfer along ...
Ahmad AL Ahmad, Reza Sirjani
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Portfolio optimization with mean-variance approach using hunting search meta-heuristic algorithm [PDF]
تحقیقات مالی, 2014 This paper presents a new meta-heuristic solution to find the efficient frontier using the mean-variance approach. Portfolio optimization problem is a quadratic programming model and, changes to NP-hard if the number of assets and constraints has ...
Morteza Elahi +2 more
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A new hybrid method DSM for parameter setting of meta-heuristic algorithms [PDF]
مجله مدل سازی در مهندسی, 2021 Parameters of meta-heuristic algorithms are very effective in their performance and are usually done experimentally, which is very time-consuming. In this research, a hybrid method for selecting the optimal parameters of meta-heuristic algorithms is ...
Elham Shadkam, Mehrnaz Ghayoor
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Meta-Heuristics: An Overview [PDF]
, 1996 Meta-heuristics are the most recent development in approximate search methods for solving complex optimization problems, that arise in business, commerce, engineering, industry, and many other areas. A meta-heuristic guides a subordinate heuristic using concepts derived from artificial intelligence, biological, mathematical, natural and physical ...
Ibrahim H. Osman, James P. Kelly
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Aerospace, 2021 This paper presents the application of an active energy management strategy to a hybrid system consisting of a proton exchange membrane fuel cell (PEMFC), battery, and supercapacitor.
Hasan Çınar, Ilyas Kandemir
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