Global-best Brain Storm Optimization Algorithm by El-Abd, Mohammed

“…Brain storm optimization (BSO) is a population-based metaheuristic algorithm that was recently developed to mimic the brainstorming process in humans. …”
Get full text
Get full text

Island flower pollination algorithm for global optimization by Al-Betar, Mohammed Azmi

“…Comparing the results of IsFPA with those of state-of-the-art methods which are FPA, genetic algorithm (GA), particle swarm optimization (PSO), gravitational search algorithm (GSA), multi-verse optimizer (MVO), island bat algorithm (iBA), and island harmony search (iHS), the comparison results show that the IsFPA is able to control the diversity and improves the outcomes where IsFPA is ranked first followed by FPA, iBA, iHS, GSA, MVO, GA, PSO, respectively, based on the Friedman test with Holm and Hochberg as post hoc statistical test.…”
Get full text
Get full text

Augmented arithmetic optimization algorithm using opposite-based learning and lévy flight distribution for global optimization and data clustering by Abu Zitar, Raed

Subjects:

Orthogonal Learning Rosenbrock’s Direct Rotation with the Gazelle Optimization Algorithm for Global Optimization by Abu Zitar, Raed

“…The gazelle optimization algorithm (GOA) is a global stochastic optimizer that is straightforward to comprehend and has powerful search capabilities. …”
Get full text

A Hybrid Flower Pollination with p-Hill Climbing Algorithm for Global Optimization by Abou Doush, Iyad

“…In this paper, the -hill climbing optimizer is hybridized with the flower pollination algorithm (FPA) as a local refinement operator for global optimization problems. …”
Get full text
Get full text

Particle swarm optimization algorithm: review and applications by Abualigah, Laith

“…Particle swarm optimization (PSO) is a heuristic global optimization technique and an optimization algorithm that is swarm intelligence-based. …”
Get full text

Segmentation of thermographies from electronic systems by using the global-best brain storm optimization algorithm by El-Abd, Mohammed

“…This paper proposes a combination of the minimum cross-entropy method and the Global-best brain storm optimization algorithm (GBSO), which improves the standard BSO to find the optimal solutions in complex search spaces. …”
Get full text
Get full text

An Intensive and Comprehensive Overview of JAYA Algorithm, its Versions and Applications by Abu Zitar, Raed

“…The JAYA algorithm combines the survival of the fittest principle from evolutionary algorithms as well as the global optimal solution attractions of Swarm Intelligence methods. …”
Get full text

Spark-based cooperative coevolution for large scale global optimization by Ahmad, Imtiaz

“…The cooperative coevolution framework was introduced to address the shortcomings of metaheuristic algorithms in solving continuous large-scale global optimization problems. …”
Get full text
Get full text

Spark-based cooperative coevolution for large scale global optimization by Ahmad, Imtiaz

“…The cooperative coevolution framework was introduced to address the shortcomings of metaheuristic algorithms in solving continuous large-scale global optimization problems. …”
Get full text
Get full text

GPU-based cooperative coevolution for large-scale global optimization by Ahmad, Imtiaz

“…The goal of researchers is to optimize the performance of algorithms in terms of both quality of solution and computational speed, seeing that large-scale optimization can be a computationally expensive process. …”
Get full text
Get full text

An Improved Genghis Khan Optimizer based on Enhanced Solution Quality Strategy for Global Optimization and Feature Selection Problems by Abdel-Salam, Mahmoud

“…Several metaheuristics, such as the Genghis Khan Shark Optimizer Algorithm (GKSO), can assist in optimizing the FS issue. …”
Get full text

A critical review and performance comparisons of swarm-based optimization algorithms in maximum power point tracking of photovoltaic systems under partial shading conditions by Muhammad Shahid Wasim (16883984)

“…The statistical analysis for 30 simulation runs shows that under heavier shading conditions, the grasshopper optimization algorithm (GOA) and salp swarm algorithm (SSA) outperform other swarm-based MPPT algorithms. …”

Optimization and control of solar-wind islanded hybrid microgrid by using heuristic and deterministic optimization algorithms and fuzzy logic controller by Sk. A., Shezan

Get full text
Get full text
Get full text

Enhancing the Local Search Ability of the Brain Storm Optimization Algorithm by Covariance Matrix Adaptation by El-Abd, Mohammed

“…However, like many other population based algorithms, BSO shows good performance at global exploration but not good enough at local exploitation. …”
Get full text
Get full text

Island artificial bee colony for global optimization by Abu Doush, Iyad

“…This paper proposes an efficient version of artificial bee colony (ABC) algorithm based on the island model concepts. The new version is called the island artificial bee colony (iABC) algorithm. …”
Get full text
Get full text

Teaching–learning-based optimization algorithm: analysis study and its application by Abualigah, Laith

Subjects: “…Teaching–learning-based optimization algorithm…”
Get full text

Optimizing MPPT Control for Enhanced Efficiency in Sustainable Photovoltaic Microgrids: A DSO-Based Approach by Debabrata Mazumdar (18560506)

“…Furthermore, an exhaustive comparative analysis has been presented among particle swarm optimization (PSO), cuckoo search algorithm (CUSA), and grey wolf optimization (GWO) under different operating environments to endorse the supremacy of the nominated technique. …”

Fuzzy Logic Adaptive Crow Search Algorithm for MPPT of a Partially Shaded Photovoltaic System by Mohamed Ali Zeddini (22047920)

Subjects:

Stochastic optimal power flow framework with incorporation of wind turbines and solar PVs using improved liver cancer algorithm by Noor Habib Khan (22224775)

“…To avoid such issues and provide the optimal solution, there are some modifications are implemented into the internal structure of t‐LCA based on Weibull flight operator, mutation‐based approach, quasi‐opposite‐based learning and gorilla troops exploitation‐based mechanisms to enhance the overall strength of the algorithm to obtain the global solution. …”