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Grey Wolf Optimization (GWO) Algorithm

2017
This chapter describes the grey wolf optimization (GWO) algorithm as one of the new meta-heuristic algorithms. First, a brief literature review is presented and then the natural process of the GWO algorithm is described. Also, the optimization process and a pseudo code of the GWO algorithm are presented in this chapter.
Hossein Rezaei   +2 more
openaire   +1 more source

Optimization of Electricity Consumption using Grey Wolf Algorithm

2020 IEEE 5th International Conference on Computing Communication and Automation (ICCCA), 2020
This paper offers optimized electricity consumption values of a smart home around the year using Grey Wolf Algorithm. The results were studied in different temperature slabs and their accuracy was found using Support Vector Machines. The motivation of doing this analysis lies behind a survey done on the same dataset using PSO and Cuckoo algorithm.
Ritika Tilwalia   +2 more
openaire   +1 more source

A Multi-Strategy Combined Grey Wolf Optimization Algorithm

2019 4th International Conference on Mechanical, Control and Computer Engineering (ICMCCE), 2019
The Grey Wolf Optimization (GWO) Algorithm is a heuristic evolutionary algorithm inspired by the hunting and leadership mechanisms of the natural grey wolf. However, its location update equation has the disadvantages of strong development ability and weak exploration ability. To improve these shortcomings, we propose the RWCA-GWO algorithm.
Jie Sun, Ming Fu
openaire   +1 more source

Grey Wolf Optimizer algorithm-based unit commitment problem

2020 Fourth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC), 2020
It is known that the electricity generator uses massive quantities of energy per year. Studies on the unit commitment problems have now been a very critical activity in a power plant. However, the current optimal solution of unit commitment problem obtained from the existing methods is very easy to collapse into a local minimum, resulting in bad ...
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Efficient computation offloading using grey wolf optimization algorithm

AIP Conference Proceedings, 2019
The widely available smart-phones as well as other mobile devices can be utilized as valuable compute resources with the support of the powerful and elastic paradigm of cloud computing. This is possible by performing computations of a limited scale on mobile devices and migrating or offloading complex services to the cloud.
Parmeet Kaur, Shikha Mehta
openaire   +1 more source

An improved grey wolf algorithm for global optimization

2018 Chinese Control And Decision Conference (CCDC), 2018
This paper presents a novel improved grey wolf optimization (IGWO) to avoid local minimization and premature convergence. In the proposed IGWO algorithm, a nonlinear control parameter based on cosine function is presented to ensure a faster convergence rate of late iteration.
Wendong Gai   +3 more
openaire   +1 more source

An Optimized Grey Wolf Algorithm

2022 IEEE International Conference on Sensing, Diagnostics, Prognostics, and Control ( SDPC), 2022
Die Zeng   +5 more
openaire   +1 more source

Congestion Management using Grey Wolf Optimization Algorithm

2022 International Conference on Advances in Computing, Communication and Materials (ICACCM), 2022
Manoj Kumar Kar   +2 more
openaire   +1 more source

Improved hybrid Jaya Grey Wolf optimization algorithm

2022 International Conference on Cloud Computing, Big Data Applications and Software Engineering (CBASE), 2022
Chu-Xin Wang   +3 more
openaire   +1 more source

A survey on Grey wolf optimization Algorithms

Grey wolf optimizer (GWO) is arising from grey wolves. The grey wolf algorithmic ruleimitate the hunting mechanism of grey wolf. This algorithmic rule is very successful inengineering field. GWO algorithmic rule is very popular in research and analyses interms of anatomy and manipulation.
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