Improved grey wolf optimisation algorithms
نویسندگان
چکیده
منابع مشابه
An Improved Bat Algorithm with Grey Wolf Optimizer for Solving Continuous Optimization Problems
Metaheuristic algorithms are used to solve NP-hard optimization problems. These algorithms have two main components, i.e. exploration and exploitation, and try to strike a balance between exploration and exploitation to achieve the best possible near-optimal solution. The bat algorithm is one of the metaheuristic algorithms with poor exploration and exploitation. In this paper, exploration and ...
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This work proposes a new meta-heuristic called Grey Wolf Optimizer (GWO) inspired by grey wolves (Canis lupus). The GWO algorithm mimics the leadership hierarchy and hunting mechanism of grey wolves in nature. Four types of grey wolves such as alpha, beta, delta, and omega are employed for simulating the leadership hierarchy. In addition, the three main steps of hunting, searching for prey, enc...
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A microwave-assisted digestion method for the determination of cadmium (Cd) and lead (Pb) by inductively coupled plasma mass spectrometry (ICP-MS) was optimised on certified reference material (CRM) (bovine liver, BCR-185R) and wolf liver samples. Different factors influencing digestion efficiency (temperature, time, composition of the digestion mixture, sample mass) were tested. Validation inc...
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Nature has always been a source of inspiration for solving complex engineering problems. It could be easily observed in the latest optimization algorithms that have been inspired by nature. Grey Wolf Optimization algorithm is a recent optimization algorithm that has been inspired by hunting behavior of grey wolves. In this paper, this algorithm has been investigated for the process of software ...
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ژورنال
عنوان ژورنال: The Journal of Engineering
سال: 2020
ISSN: 2051-3305,2051-3305
DOI: 10.1049/joe.2019.1174