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A parallel implementation of ant colony optimization [PDF]
, 2002 Ant Colony Optimization is a relatively new class of meta-heuristic search techniques for optimization problems. As it is a population-based technique that examines numerous solution options at each step of the algorithm, there are a variety of ...
Lewis, A., Randall, M
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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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Meta-heuristic Algorithms for Nesting Problem of Rectangular Pieces [PDF]
, 2017 Nesting problems consist of placing multiple items onto larger shapes finding a good arrangement. The goal of the nesting process is to minimize the waste of material.
Lo Valvo, E.
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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 portfolio optimization
Soft Computing, 2023 AbstractPortfolio optimization has been studied extensively by researchers in computer science and finance, with new and novel work frequently published. Traditional methods, such as quadratic programming, are not computationally effective for solving complex portfolio models.
Kyle Erwin, Andries Engelbrecht
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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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Jamming Model for the Extremal Optimization Heuristic [PDF]
, 2001 Extremal Optimization, a recently introduced meta-heuristic for hard optimization problems, is analyzed on a simple model of jamming. The model is motivated first by the problem of finding lowest energy configurations for a disordered spin system on a ...
+20 more
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Meta-heuristics and Artificial Intelligence [PDF]
, 2020 Meta-heuristics are generic search methods that are used to solve challenging combinatorial problems. We describe these methods and highlight their common features and differences by grouping them in two main kinds of approaches: Perturbative meta-heuristics that build new combinations by modifying existing combinations (such as, for example, genetic ...
Hao, Jin-Kao, Solnon, Christine
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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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