Search Results - subject:"optimizer"

A comparative analysis of preying behavior-based metaheuristic algorithms for optimization of laser beam drilling processes

Pendokhare, Devendra; Chakraborty, Shankar - 2024

-based metaheuristic algorithms, i.e., sailfish optimizer, Harris hawks optimizer, Aquila optimizer, bat optimizer, and grey wolf optimizer … solutions, convergence speed and computational effort, identifying grey wolf optimizer as the most efficient one. The results of … Friedman's mean rank test also prove the superiority of grey wolf optimizer over its competitors. …

Persistent link: https://www.econbiz.de/10014541921

A mixed-integer non-linear no-wait open-shop scheduling model for minimizing makespan and total tardiness in manufacturing

Mirmozaffari, Mirpouya; Hejazi, Seyed Mojtaba; … - 2024

address smaller-scale instances of these problems. Three metaheuristic algorithms of Grey Wolf Optimizer (GWO), Whale … Optimization Algorithm (WOA), and Ant Lion Optimizer (ALO) are compared to resolve large-scale problems by considering a sorting … 250 iterations. Since metaheuristics are a theoretically powerful optimizer tool designed to expedite the resolution of …

Persistent link: https://www.econbiz.de/10014541881

Optimizing solar photovoltaic power forecasting via multi-architecture machine learning framework with multiple hyperparameter optimization techniques

Tahir, Muhammad Faizan; Tzes, Anthony; El-Fouly, Tarek H. M. - In: Energy strategy reviews 61 (2025), pp. 1-20

-structured Parzen Estimator, Bayesian optimization, random search with successive halving, and grey wolf optimizer. The performance of …

Persistent link: https://www.econbiz.de/10015485825

A new grey seasonal multivariate forecasting model and its application in energy consumption

Jiang, Jianming; Ban, Yandong; Zhang, Ming; Qu, Chiwen - In: Energy strategy reviews 59 (2025), pp. 1-8

Accurate energy consumption forecasting is of critical importance, as it enables governments, industries, and individuals to effectively plan for energy supply and demand, thereby reducing the risks associated with both oversupply and shortages. While prior research has explored various...

Persistent link: https://www.econbiz.de/10015458245

Resilient COVID-19 vaccine supply chain : an optimization and simulation approach for multi-objective management

Khalilpoor, Saeedeh; Kamran, Mehdi A.; Solimanpur, Maghsud - In: Transportation research : an international journal 201 (2025), pp. 1-38

Persistent link: https://www.econbiz.de/10015451707

Forecasting of natural gas based on a novel discrete grey seasonal prediction model with a time power term

Zhang, Jun; Shen, Chaofeng; Qin, Yanping; Chen, Jingyi - In: Energy strategy reviews 58 (2025), pp. 1-15

To effectively manage natural gas dispatchability, the energy industry needs to precisely analyze the seasonal trends of natural gas production and consumption. However, most predictive models demand data pretreatment and are labor-intensive. To address this, a novel seasonal discrete grey...

Persistent link: https://www.econbiz.de/10015437371

An optimization of multi-level multi-objective cloud production systems with meta-heuristic algorithms

Razdar, Mohammadreza; Adibi, Mohammad Amin; Haleh, Hassan - 2025

-objective grey wolf optimizer (MOGWO), and non-dominated sorting genetic algorithm-II (NSGA-II) algorithms were used to solve the …

Persistent link: https://www.econbiz.de/10015420123

Research and application of a novel grey multivariable model in port scale prediction under the impact of Free Trade Zone

Sun, Yuyu; Zhang, Yuchen; Zhao, Zhiguo - In: Marine economics and management : MAEM 7 (2024) 1, pp. 79-101

Purpose - Considering the impact of the Free Trade Zone (FTZ) policy on forecasting the port cargo throughput, this paper constructs a fractional grey multivariate forecasting model to improve the prediction accuracy of port cargo throughput and realize the coordinated development of FTZ...

Persistent link: https://www.econbiz.de/10015046359

A systematic review of hyperparameter optimization techniques in Convolutional Neural Networks

Raiaan, Mohaimenul Azam Khan; Sakib, Sadman; Fahad, Nur … - 2024

Convolutional Neural Network (CNN) is a prevalent topic in deep learning (DL) research for their architectural advantages. CNN relies heavily on hyperparameter configurations, and manually tuning these hyperparameters can be time-consuming for researchers, therefore we need efficient...

Persistent link: https://www.econbiz.de/10015101999

A constrained swarm optimization algorithm for large-scale long-run investments using Sharpe ratio-based performance measures

Kaucic, Massimiliano; Piccotto, Filippo; Sbaiz, Gabriele - In: Computational management science 21 (2024) 1, pp. 1-29

Persistent link: https://www.econbiz.de/10014442612

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