Gravitational search algorithm: Theory, literature review, and applications
A Hashemi, MB Dowlatshahi… - Handbook of AI-based …, 2021 - taylorfrancis.com
Today, many metaheuristics algorithms have been developed are inspired by the physical
phenomena or behaviors of natural creatures that are very effective in solving complex …
phenomena or behaviors of natural creatures that are very effective in solving complex …
Optimizing the parameters of hybrid active power filters through a comprehensive and dynamic multi-swarm gravitational search algorithm
This paper introduces a dynamic comprehensive multi-swarm gravitational search algorithm
with non-uniform mutation (cdGSA-2m) for optimizing hybrid active power filter (HAPF) …
with non-uniform mutation (cdGSA-2m) for optimizing hybrid active power filter (HAPF) …
Artificial electric field algorithm for engineering optimization problems
Nature-inspired optimization algorithms have attracted significant attention from researchers
during the past decades due to their applicability to solving the challenging optimization …
during the past decades due to their applicability to solving the challenging optimization …
Comprehensive learning Harris hawks-equilibrium optimization with terminal replacement mechanism for constrained optimization problems
C Zhong, G Li - Expert Systems with Applications, 2022 - Elsevier
Harris hawks optimization (HHO) is a novel metaheuristic algorithm which has strong
convergence for unconstrained optimization problems. However, HHO may encounter …
convergence for unconstrained optimization problems. However, HHO may encounter …
A hybrid teaching–learning slime mould algorithm for global optimization and reliability-based design optimization problems
Slime mould algorithm (SMA) is a novel metaheuristic algorithm with good performance for
optimization problems, but it may encounter premature or low accuracy in complex …
optimization problems, but it may encounter premature or low accuracy in complex …
Application of effective gravitational search algorithm with constraint priority and expert experience in optimal allocation problems of distribution network
J Qian, P Wang, C Pu, X Peng, G Chen - Engineering Applications of …, 2023 - Elsevier
Optimal allocation problem of distribution network (OAPDN), which attracts much attention of
electric enterprise, contributes to the flexible and environmental-friendly power supply by …
electric enterprise, contributes to the flexible and environmental-friendly power supply by …
An adaptive artificial electric field algorithm for continuous optimization problems
The comprehensive learning strategy is a meticulous method for enhancing the optimization
ability of population‐based optimization algorithms. This article proposes an adaptive …
ability of population‐based optimization algorithms. This article proposes an adaptive …
A crossover-based optimization algorithm for multilevel image segmentation
Image segmentation plays a pivotal role in numerous image processing applications, with
Kapur-and Otsu-based methods frequently applied for bi-level thresholding. However …
Kapur-and Otsu-based methods frequently applied for bi-level thresholding. However …
Humanoid robot path planning using memory-based gravity search algorithm and enhanced differential evolution approach in a complex environment
DR Parhi, AK Kashyap - Expert Systems with Applications, 2023 - Elsevier
The present work focuses on the optimal path planning of humanoid robots in a rugged
terrain using a hybrid-based improved gravitational search algorithm (IGSA) tuned with a …
terrain using a hybrid-based improved gravitational search algorithm (IGSA) tuned with a …
Binary artificial electric field algorithm
Abstract Artificial Electric Field Algorithm (AEFA) is one of the recent population-based
optimization techniques, it is inspired by the electrostatic force theory. This article aims to …
optimization techniques, it is inspired by the electrostatic force theory. This article aims to …