Grey Wolf Optimizer

Mirjalili, Seyedali; Mirjalili, Seyed Mohammad; Lewis, Andrew

doi:10.1016/j.advengsoft.2013.12.007

Cited by 12,070 publications

(5,369 citation statements)

References 73 publications

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“…Wolf packs own one of the most well-organized social interactions for hunting. Grey wolf optimization was proposed by Mirjalili et al (2014). Mirjalili creates a bio-inspired optimization algorithm, the so called grey wolf optimization (GWO), which has been inspired from the leadership hierarchy and hunting mechanism of grey wolves in nature.…”

Section: Grey Wolf Optimization (Gwo)mentioning

confidence: 99%

“…(16) and (17). The encircling behavior of grey wolves can be represented as : (Mirjalili et al 2014)…”

Section: Encircling Preymentioning

confidence: 99%

“…Then, he proved the grey wolf optimizer results were able to provide highly competitive results compared to well-known heuristics such as PSO, GSA, DE, EP, and ES . In addition, the three main steps of hunting, searching for prey, encircling prey, and attacking prey, are implemented (Mirjalili et al 2014). …”

Section: Grey Wolf Optimization (Gwo)mentioning

confidence: 99%

“…It has been shown that the grey wolf optimizer algorithm is able to provide very competitive results compared to other well-known meta-heuristics. The grey wolf optimizer algorithm has been successfully applied to three classical engineering design problems and real optical engineering (Mirjalili et al 2014). Song et al (2014) have successfully applied GWO for solving combined economic emission dispatch problems.…”

mentioning

confidence: 99%

“…They used swarm intelligence algorithms in this research. Mirjalili et al (2014) have recently tested grey wolf optimizer (GWO) on uni-modal, multi-modal, fixed-dimension multimodal, and composite functions. It is efficient in terms of exploration, exploitation, local optimal avoidance, and convergence.…”

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confidence: 99%

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Optimum Design of Effective Parameters for Orthotropic Plates with Polygonal Cut-Out

Jafari

Chaleshtari

2017

Lat. Am. j. solids struct.

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This paper investigates the effect of different parameters on stress analysis of infinite orthotropic plates with central polygonal cutout using gray wolf optimization algorithm. The important features of gray wolf algorithm include flexibility, simplicity, short solution time and ability to avoid local optimums. The effective parameters on stress distribution around cutouts include load angle, curvature radius of the corner of the cutout, cutout orientation and fiber angle for orthotropic materials. The used analytical solution is the expansion of Lekhnitskii's solution method. The effect of the aforementioned parameters on the stress distribution around triangular, square, pentagonal and hexagonal cutout is examined. The results showed that these parameters have significant effects on stress distribution around the cutouts and the structural loadbearing capacity will increase without changing the type of material if the parameters are correctly chosen.

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Section: Grey Wolf Optimization (Gwo)mentioning

confidence: 99%

“…(16) and (17). The encircling behavior of grey wolves can be represented as : (Mirjalili et al 2014)…”

Section: Encircling Preymentioning

confidence: 99%

Section: Grey Wolf Optimization (Gwo)mentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Optimum Design of Effective Parameters for Orthotropic Plates with Polygonal Cut-Out

Jafari

Chaleshtari

2017

Lat. Am. j. solids struct.

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Robust coordinated control for damping low frequency oscillations in high wind penetration power system

Gupta

Verma

Niazi

2019

Int Trans Electr Energ Syst

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The preeminence of wind power as a source of clean power generation is growing very fast. The increasing wind penetration, however, escalates the problem of low‐frequency oscillations (LFOs) in the modern grid. In this paper, LFOs damping improvement is presented for a high wind penetration power system by a robust coordinated control strategy of the power system stabilizer (PSS) and power oscillation damper (POD) of doubly fed induction generator (DFIG). This control strategy is achieved using an improved eigenvalue‐based objective function, optimized using grey wolf optimizer (GWO). The impact of wind farm location on system oscillatory stability is accomplished using eigenvalue analysis and dynamic sensitivity analysis. The wide‐area‐based phasor measurement unit (PMU) signals are used as PODs input selected using modal observability criterion. The eigenvalue analysis, time‐domain simulations, and robustness analysis are performed to verify the efficacy of the proposed control strategy on a modified IEEE New England test system. The simulation results show the improvement in LFO damping with the proposed control strategy for a wide range of operating scenarios including faults and line outages at different loading conditions.

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Optimal size of photovoltaic pumping system using nature‐inspired algorithms

Bakelli

Kaabeche

2019

Int Trans Electr Energ Syst

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Summary In this article, an optimal design model using metaheuristic techniques to overcome such difficult optimization problems has been proposed. For this purpose, various well‐known metaheuristic algorithms have been used, namely: ant lion optimizer (ALO), bat algorithm (BA), cuckoo search algorithm (CSA), and gray wolf optimization algorithm (GWO). To provide optimal system configurations, an objective function based on the total net present cost (TNPC) has been specified while taking into account a number of constraints, including the loss of power supply probability (LPSP). The effectiveness of the used algorithms in solving such problem is assessed and their performances compared with each other. To assess the suggested model's effectiveness, a case study has been conducted to investigate a stand‐alone photovoltaic water pumping system (PVWPS), designed to supply water to a one‐hectare field of date palm trees. This field of an oasis located in the Ghardaïa region of Algeria consists of 130 date palm trees spaced 9 m apart. The simulation results show the effectiveness of the GWO algorithm over the other algorithms. GWO converges toward the optimal solutions for different heads and all reliability levels required by the customer. Another aspect, supported by the developed methodology, is the accounting of the excess water volume. It has been found that the relative surplus is inversely proportional to the PVWPS reliability level. For a head of 30 m, the relative excess is estimated at 120% for LPS0%, while it is 27% for LPSP of 10%. The same observations are made for the other heads.

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Grey Wolf Optimizer

Cited by 12,070 publications

References 73 publications

Optimum Design of Effective Parameters for Orthotropic Plates with Polygonal Cut-Out

Optimum Design of Effective Parameters for Orthotropic Plates with Polygonal Cut-Out

Robust coordinated control for damping low frequency oscillations in high wind penetration power system

Optimal size of photovoltaic pumping system using nature‐inspired algorithms

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