Improved Grey Wolf Optimization Algorithm and Application. [PDF]
Sensors (Basel), 2022 This paper proposed an improved Grey Wolf Optimizer (GWO) to resolve the problem of instability and convergence accuracy when GWO is used as a meta-heuristic algorithm with strong optimal search capability in the path planning for mobile robots. We improved chaotic tent mapping to initialize the wolves to enhance the global search ability and used a ...
Hou Y, Gao H, Wang Z, Du C.
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Grey Wolf Optimization algorithm based on Cauchy-Gaussian mutation and improved search strategy [PDF]
Scientific Reports, 2022 The traditional Grey Wolf Optimization algorithm (GWO) has received widespread attention due to features of strong convergence performance, few parameters, and easy implementation.
Kewen Li +4 more
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Improved grey wolf algorithm for optimization problems [PDF]
Indonesian Journal of Electrical Engineering and Computer Science, 2021 The grey wolf optimization (GWO) is a nature inspired and meta-heuristic algorithm, it has successfully solved many optimization problems and give better solution as compare to other algorithms.
Aamir, Muhammad +3 more
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Hybrid optimization algorithm for solving path planning problems based on grey wolf optimization algorithm [PDF]
Scientific ReportsThe grey wolf optimization algorithm is a metaheuristic optimization algorithm based on the behavior of grey wolf groups in nature, which has the advantages of a simple concept and few adjustment parameters and is widely used in various fields.
Gang Cheng, Yadong Liu
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A Novel Complex-Valued Encoding Grey Wolf Optimization Algorithm [PDF]
Algorithms, 2015 Grey wolf optimization (GWO) is one of the recently proposed heuristic algorithms imitating the leadership hierarchy and hunting mechanism of grey wolves in nature. The aim of these algorithms is to perform global optimization.
Qifang Luo +3 more
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An Improved Grey Wolf Optimization Algorithm with Variable Weights. [PDF]
Comput Intell Neurosci, 2019 With a hypothesis that the social hierarchy of the grey wolves would be also followed in their searching positions, an improved grey wolf optimization (GWO) algorithm with variable weights (VW-GWO) is proposed. And to reduce the probability of being trapped in local optima, a new governing equation of the controlling parameter is also proposed ...
Gao ZM, Zhao J.
europepmc +3 more sources
A Virtual Force Algorithm-Lévy-Embedded Grey Wolf Optimization Algorithm for Wireless Sensor Network Coverage Optimization [PDF]
Sensors, 2019 The random placement of a large-scale sensor network in an outdoor environment often causes low coverage. In order to effectively improve the coverage of a wireless sensor network in the monitoring area, a coverage optimization algorithm for wireless ...
Shipeng Wang +3 more
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A Novel Hybrid Algorithm Based on Grey Wolf Optimizer and Fireworks Algorithm [PDF]
Sensors, 2020 Grey wolf optimizer (GWO) is a meta-heuristic algorithm inspired by the hierarchy of grey wolves (Canis lupus). Fireworks algorithm (FWA) is a nature-inspired optimization method mimicking the explosion process of fireworks for optimization problems ...
Zhihang Yue, Sen Zhang, Wendong Xiao
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Chain hybrid feature selection algorithm based on improved Grey Wolf Optimization algorithm. [PDF]
PLoS OneHybrid feature selection algorithm is a strategy that combines different feature selection methods aiming to overcome the limitations of a single feature selection method and improve the effectiveness and performance of feature selection. In this paper, we propose a new hybrid feature selection algorithm, to be named as Tandem Maximum Kendall Minimum ...
Bai X, Zheng Y, Lu Y, Shi Y.
europepmc +4 more sources
A Novel Dynamic Generalized Opposition-Based Grey Wolf Optimization Algorithm [PDF]
Algorithms, 2018 To enhance the convergence speed and calculation precision of the grey wolf optimization algorithm (GWO), this paper proposes a dynamic generalized opposition-based grey wolf optimization algorithm (DOGWO). A dynamic generalized opposition-based learning
Yanzhen Xing, Donghui Wang, Leiou Wang
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