Wild Geese Algorithm: A novel algorithm for large scale optimization based on the natural life and death of wild geese

Ghasemi, Maryam; Rahimnejad, Abolfazl; Hemmati, Rasul; Akbari, Ebrahim; Gadsden, S. Andrew

doi:10.1016/j.array.2021.100074

Cited by 39 publications

(16 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Wild geese algorithm (WGA) is a recent metaheuristic algorithm that is taken from the idea of coordination in migration, food searching and mortality of wild geese [18]. WGA has demonstrated its ability for finding the optimal value of test functions [18]. However, its performance for the BESS problem is still a question.…”

Section: Issn: 2302-9285 mentioning

confidence: 99%

See 1 more Smart Citation

Minimizing electricity cost by optimal location and power of battery energy storage system using wild geese algorithm

Nguyen

2023

Bulletin EEI

View full text Add to dashboard Cite

The mismatch between load demand and supply power may increase when distributed generation based on renewable energy sources is connected to the distribution system (DS). This paper shows the optimal battery energy storage system (BESS) placement problem on the DS to minimize the electricity cost. Diverse electricity prices are considered for normal, off-peak and peak hours in a day. Wild geese algorithm (WGA) is applied to optimize the location and power of the BESS. The problem and the efficiency of WGA is validated on the 18-bus DS four scenarios consisting of the DS without BESS placement, the DS with BESS placement, the DS existing photovoltaic system (PVS) without BESS placement and the DS existing PVS with BESS placement. The numerical results show that optimal BESS placement is an effective solution for minimizing electricity cost on the DS with and without PVS. In addition, the results have also shown that WGA is a potential method for the BESS placement problem.

show abstract

Section: Issn: 2302-9285 mentioning

confidence: 99%

“…Step 4: decrease the population size. The weaker goose in the population will be died and the population size will be reduced to the final number of geese (𝑁 𝑓𝑖𝑛𝑎𝑙 ) as (18):…”

Section: Wga For Optimal Location and Power Of Bessmentioning

confidence: 99%

Minimizing electricity cost by optimal location and power of battery energy storage system using wild geese algorithm

Nguyen

2023

Bulletin EEI

View full text Add to dashboard Cite

show abstract

“…FGBO has four stages, namely, league holding, player transfer, practice, and promotion and relegation [60]. Wild geese algorithm (WGA) mimics the natural life and death of wild geese [61].Aquila optimizer (AO) imitates the foraging behavior of Aquila [62]. Hunger games search (HGS) is another algorithm that makes use of huger driven connections [63].…”

Section: Neural Computing and Applicationsmentioning

confidence: 99%

A novel metaheuristic algorithm inspired by COVID-19 for real-parameter optimization

Mohammadi

Nazarpour

Beiraghi

2023

Neural Comput & Applic

View full text Add to dashboard Cite

In this modern world, we are encountered with numerous complex and emerging problems. The metaheuristic optimization science plays a key role in many fields from medicine to engineering, design, etc. Metaheuristic algorithms inspired by nature are among the most effective and fastest optimization methods utilized to optimize different objective functions to minimize or maximize one or more specific objectives. The use of metaheuristic algorithms and their modified versions is expanding every day. However, due to the abundance and complexity of various problems in the real world, it is always necessary to select the most proper metaheuristic method; hence, there is a strong need to create new algorithms to achieve our desired goal. In this paper, a new and powerful metaheuristic algorithm, called the coronavirus metamorphosis optimization algorithm (CMOA), is proposed based on metabolism and transformation under various conditions. The proposed CMOA algorithm has been tested and implemented on the comprehensive and complex CEC2014 benchmark functions, which are functions based on real-world problems. The results of the experiments in a comparative study under the same conditions show that the CMOA is superior to the newly-developed metaheuristic algorithms including AIDO,

show abstract

“…The displacement and velocity formula in relation to the geese's coordinated velocity is described in the equations below [ 38 ]. …”

Section: Proposed Approachmentioning

confidence: 99%

Multithreshold Image Segmentation Technique Using Remora Optimization Algorithm for Diabetic Retinopathy Detection from Fundus Images

Vinayaki

Kalaiselvi

2022

Neural Process Lett

View full text Add to dashboard Cite

One of the most common complications of diabetes mellitus is diabetic retinopathy (DR), which produces lesions on the retina. A novel framework for DR detection and classification was proposed in this study. The proposed work includes four stages: pre-processing, segmentation, feature extraction, and classification. Initially, the image pre-processing is performed and after that, the Multi threshold-based Remora Optimization (MTRO) algorithm performs the vessel segmentation. The feature extraction and classification process are done by using a Region-based Convolution Neural Network (R-CNN) with Wild Geese Algorithm (WGA). Finally, the proposed R-CNN with WGA effectively classifies the different stages of DR including Non-DR, Proliferative DR, Severe, Moderate DR, Mild DR. The experimental images were collected from the DRIVE database, and the proposed framework exhibited superior DR detection performance. Compared to other existing methods like fully convolutional deep neural network (FCDNN), genetic-search feature selection (GSFS), Convolutional Neural Networks (CNN), and deep learning (DL) techniques, the proposed R-CNN with WGA provided 95.42% accuracy, 93.10% specificity, 93.20% sensitivity, and 98.28% F-score results.

show abstract

Wild Geese Algorithm: A novel algorithm for large scale optimization based on the natural life and death of wild geese

Cited by 39 publications

References 31 publications

Minimizing electricity cost by optimal location and power of battery energy storage system using wild geese algorithm

Minimizing electricity cost by optimal location and power of battery energy storage system using wild geese algorithm

A novel metaheuristic algorithm inspired by COVID-19 for real-parameter optimization

Multithreshold Image Segmentation Technique Using Remora Optimization Algorithm for Diabetic Retinopathy Detection from Fundus Images

Contact Info

Product

Resources

About