Surrogate-Assisted Hybrid Meta-Heuristic Algorithm with an Add-Point Strategy for a Wireless Sensor Network [PDF]
Entropy, 2023 Meta-heuristic algorithms are widely used in complex problems that cannot be solved by traditional computing methods due to their powerful optimization capabilities. However, for high-complexity problems, the fitness function evaluation may take hours or
Jeng-Shyang Pan +4 more
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A new meta-heuristic algorithm: military optimization algorithm (MOA) [PDF]
تصمیم گیری و تحقیق در عملیات, 2021 Purpose: In recent years, meta-heuristic algorithms and their application in solving complicated, nonlinear, and high dimensions problems have increased dramatically and the fact that meta-heuristic algorithms are used to solve complex and changing ...
Hojatollah Rajabi Moshtaghi +2 more
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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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A Novel Hybrid Meta-Heuristic Algorithm Based on the Cross-Entropy Method and Firefly Algorithm for Global Optimization. [PDF]
Entropy (Basel), 2019 Li G, Liu P, Le C, Zhou B.
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A Hybrid Artificial Grasshopper Optimization (HAGOA) Meta-Heuristic Approach: A Hybrid Optimizer For Discover the Global Optimum in Given Search Space [PDF]
International Journal of Mathematical, Engineering and Management Sciences, 2019 Meta-heuristic algorithms are used to get optimal solutions in different engineering branches. Here four types of meta-heuristics algorithms are used such as evolutionary algorithms, swarm-based algorithms, physics based algorithms and human based ...
Brahm Prakash Dahiya +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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Alexandria Engineering Journal, 2023 Meta heuristics is an optimization approach that works as an intelligent technique to solve optimization problems. Evolutionary algorithms, human-based algorithms, physics-based algorithms and swarm intelligence are categorized under meta-heuristic ...
Othman Waleed Khalid +2 more
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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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IET Software, 2021 In this research, a new method for population initialisation in meta‐heuristic algorithms based on the Pareto 80/20 rule is presented. The population in a meta‐heuristic algorithm has two important tasks, including pushing the algorithm toward the real ...
Mohammad Reza Hasanzadeh, Farshid Keynia
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An Opposition-Based Chaotic Salp Swarm Algorithm for Global Optimization
IEEE Access, 2020 The salp swarm algorithm (SSA) is a bio-heuristic optimization algorithm proposed in 2017. It has been proved that SSA has competitive results compared to several other well-known meta-heuristic algorithms on various optimization problem.
Xiaoqiang Zhao +3 more
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