A Hybrid Algorithm based on Invasive Weed Optimization and Particle Swarm Optimization for Global Optimization
نویسندگان
چکیده
منابع مشابه
A Hybrid Algorithm based on Invasive Weed Optimization and Particle Swarm Optimization for Global Optimization
In this paper, an effective combination of two Metaheuristic algorithms, namely Invasive Weed Optimization and the Particle Swarm Optimization, has been proposed. This hybridization called as HIWOPSO, consists of two main phases of Invasive Weed Optimization (IWO) and Particle Swarm Optimization (PSO). Invasive weed optimization is the natureinspired algorithm which is inspired by colonial beha...
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Particle Swarm Optimization (PSO) is a bioinspired meta-heuristic for solving complex global optimization problems. In standard PSO, the particle swarm frequently gets attracted by suboptimal solutions, causing premature convergence of the algorithm and swarm stagnation. Once the particles have been attracted to a local optimum, they continue the search process within a minuscule region of the ...
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Particle swarm optimization (PSO) and differential evolution (DE) are both efficient and powerful population-based stochastic search techniques for solving optimization problems, which have been widely applied in many scientific and engineering fields. Unfortunately, both of them can easily fly into local optima and lack the ability of jumping out of local optima. A novel adaptive hybrid algori...
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Particle Swarm Optimization (PSO) is a recently developed optimization method, which has attracted interest of researchers in various areas due to its simplicity and effectiveness, and many variants have been proposed. In this paper, a novel Particle Swarm Optimization algorithm is presented, in which the information of the best neighbor of each particle and the best particle of the entire popu...
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ژورنال
عنوان ژورنال: International Journal of Advanced Computer Science and Applications
سال: 2016
ISSN: 2156-5570,2158-107X
DOI: 10.14569/ijacsa.2016.071040