An Optimal Distillation Process for Turpentine Separation Using a Firefly Algorithm by Gustavo Mendes Platt, Otávio Knevitz de Azevedo, Francisco Bruno Souza Oliveira

“…The results show that the tool developed—together with the Firefly algorithm—is capable of obtaining optimized results (although there is no guarantee of a global optimum) from a small set of initial design configurations.…”
Get full text

Two-Stage Genetic Algorithm for Optimization Logistics Network for Groupage Delivery by Ivan P. Malashin, Vadim S. Tynchenko, Igor S. Masich, Denis A. Sukhanov, Daniel A. Ageev, Vladimir A. Nelyub, Andrei P. Gantimurov, Alexey S. Borodulin

“…This study explored the optimization of groupage intercity delivery using a two-stage genetic algorithm (GA) framework, developed with the BaumEvA Python library. …”
Get full text

The WSN Localization Algorithm Integrating Ranging Correction and Spider Wasp Optimization by YU Xiu-wu, XIAO Lin, LIU Yong, YE Lai

“…This paper proposes a modified DV-Hop algorithm that integrates distance correction and a Spider Wasp Optimization (SWO) algorithm to address these issues. …”
Get full text

Damage Detection of Steel Roof Systems Using Planet Optimization Algorithm by Thanh Sang-To, Van The Huy-Nguyen, Samir Khatir, The Vi-Huynh, Hoang Le-Minh, Thanh Cuong-Le

“…The achieved results illustrate that in terms of stability, robustness, and quality of the obtained solution, POA is one of most outstanding optimization algorithms. POA ranks No. 1 in functions F1, F4, F7, F8, F13, while POA is highly ranked and sufficiently competitive with the other contenders in the rest of tests. …”
Get full text

Genetic Algorithm for Optimal Control Design to Gust Response for Elastic Aircraft by Mauro Iavarone, Umberto Papa, Alberto Chiesa, Luca de Pasquale, Angelo Lerro

Get full text

Optimization of the Offshore Wind Turbines Layout Using Cuckoo Search Algorithm by Ibrahim Abdulwahab, Solomon Andrew Onazi, Gideon Rimamfate, Akande Abdulwasiu, Abubakar Umar, N.A Iliyasu

“…After-which a cuckoo search algorithm technique is employed in the wind farm model to optimize the optimization problem (minimizing the wake effect while improving power output and cost). …”
Get full text

Optimal performance design of bat algorithm: An adaptive multi‐stage structure by Helong Yu, Jiuman Song, Chengcheng Chen, Ali Asghar Heidari, Yuntao Ma, Huiling Chen, Yudong Zhang

“…Abstract The bat algorithm (BA) is a metaheuristic algorithm for global optimisation that simulates the echolocation behaviour of bats with varying pulse rates of emission and loudness, which can be used to find the globally optimal solutions for various optimisation problems. …”
Get full text

Causal Diagnosability Optimization Design for UAVs Based on Maximum Mean Covariance Difference and the Gray Wolf Optimization Algorithm by Xuping Gu, Xianjun Shi

“…Finally, a diagnosability optimization technique utilizing the GWO algorithm is proposed. …”
Get full text

Investigation of a Multi-Strategy Ensemble Social Group Optimization Algorithm for the Optimization of Energy Management in Electric Vehicles by Aala Kalananda Vamsi Krishna Reddy, Komanapalli Venkata Lakshmi Narayana

“…A multi-strategy ensemble social group optimization algorithm (ME-SGO) to improve the exploration for complex and composite landscapes through distance-based strategy adaption and success-based parameter adaption while incorporating linear population reduction is proposed. …”
Get full text

Scheduling optimization based on particle swarm optimization algorithm in emergency management of long-distance natural gas pipelines. by Huichao Guo, Runhua Huang, Shuqin Cheng

“…The experimental results show that compared with the traditional particle swarm optimization algorithm, NACFPSO performs well in both convergence speed and scheduling time, with an average convergence speed of 81.17 iterations and an average scheduling time of 200.00 minutes; while the average convergence speed of the particle swarm optimization algorithm is 82.17 iterations and an average scheduling time of 207.49 minutes. …”
Get full text

An Improved Particle Swarm Optimization Algorithm forOptimal Allocation of Distributed Generation Units in Radial Power Systems by Neda Hantash, Tamer Khatib, Maher Khammash

“…The minimum value of fitness losses using the applied algorithm is found to be 0.0.0406 while the average elapsed time is 62.2325 s. …”
Get full text

RUL Prediction of Rolling Bearings Based on Fruit Fly Optimization Algorithm Optimized CNN-LSTM Neural Network by Jiaping Shen, Haiting Zhou, Muda Jin, Zhongping Jin, Qiang Wang, Yanchun Mu, Zhiming Hong

“…In addition, introducing FOA enables the model to dynamically adjust the hidden layers and thresholds while optimizing the optimal path, thereby finding the best solution. …”
Get full text

Optimized conductor selection and phase balancing in unbalanced distribution networks: Economic optimization via the vortex search algorithm by Brandon Cortés-Caicedo, Jhony Andrés Guzmán-Henao, Oscar Danilo Montoya, Luis Fernando Grisales-Noreña, Rubén Iván Bolaños

“…This methodology is compared against the hurricane optimization algorithm, the sine cosine algorithm, and the salp swarm optimization algorithm. …”
Get full text

Optimizing energy constrained target localization and tracking with radial bias and seeker optimization algorithms in wireless sensor networks by S. Yazhinian, S. Famila, P. Jose, Mahendar A, Sofia R

“…This paper proposes a novel approach combining Radial Bias (RB) with the Seeker Optimization Algorithm (SOA) to address the challenges of energy-constrained target localization and tracking. …”
Get full text

Energy-Efficient DC Power Traction Network Systems for Urban Mass Transportation: A Comparative Study of Optimization Algorithms by Dongxian Yu, Zhixin Wu, Lei Wang, Zaihui Cao, Hamdolah Aliev

“…To validate the proposed method, we compare the performance of the GWO algorithm with other optimization techniques, such as the Teaching-Learning-Based Optimizer (TLBO) and Differential Evolution (DE). …”
Get full text

Many-Objective Cheetah Optimizer: A Novel Paradigm for Solving Complex Engineering Problems by Pinank Patel, Divya Adalja, Nikunj Mashru, Pradeep Jangir, Arpita, Reena Jangid, G. Gulothungan, Ahmad O. Hourani, Kaznah Alshammari

“…MaOCO represents the Many-Objective Cheetah Optimization Algorithm which draws its concepts from the hunting behavior of cheetahs. …”
Get full text

Improving aquifer vulnerability assessment and its explainability in the Zanjan aquifer: Integrating DRASTIC model and optimized long short-term memory-based metaheuristic algorith... by Mojgan Bordbar, Khabat Khosravi, Changhyun Jun, Dongkyun Kim, Sayed M Bateni, Mahmood Safarzadeh, Hamid Kardan Moghaddam, Shohreh Azizi

“…The LSTM model was optimized using the particle swarm optimizer (PSO) and equilibrium optimizer (EO) metaheuristic algorithms. …”
Get full text

Rethinking Metaheuristics: Unveiling the Myth of “Novelty” in Metaheuristic Algorithms by Chia-Hung Wang, Kun Hu, Xiaojing Wu, Yufeng Ou

“…While nature-inspired optimization methods show promise for various applications, their effectiveness is often limited by metaphor-driven design, structural biases, and a lack of sufficient theoretical foundation. …”
Get full text

An efficient enhanced exponential distribution optimizer: applications in global, engineering, and combinatorial optimization problems by Marwa M. Emam, Mohammed R. Saad, Mina Younan, Essam H. Houssein

“…The optimizers include the improved multi-operator differential evolution algorithm (IMODE), adaptive guided differential evolution algorithm (AGDE), whale optimization algorithm (WOA), grey wolf optimizer (GWO), sinh cosh optimizer (SCHO), RIME optimization algorithm (RIME), and the original EDO. …”
Get full text

An improved dung beetle optimizer based on Padé approximation strategy for global optimization and feature selection by Tianbao Liu, Lingling Yang, Yue Li, Xiwen Qin

“…Feature selection is a crucial data processing method used to reduce dataset dimensionality while preserving key information. In this paper, we proposed a multi-strategy enhanced dung beetle optimization algorithm (mDBO) that integrates multiple strategies to effectively address the feature selection problem. …”
Get full text