Hierarchical parallel search with automatic parameter configuration for particle swarm optimization
F Zhao, F Ji, T Xu, N Zhu - Applied Soft Computing, 2024 - Elsevier
Particle swarm optimization (PSO) has been widely applied in solving optimization
problems. Despite a multitude of PSO variants that have been proposed thus far, they still …
problems. Despite a multitude of PSO variants that have been proposed thus far, they still …
[HTML][HTML] Scheduling in manufacturing with transportation: Classification and solution techniques
Many modern manufacturing settings feature especially close relationship of the
transportation of workpieces between production steps with the scheduling of manufacturing …
transportation of workpieces between production steps with the scheduling of manufacturing …
PSCSO: Enhanced sand cat swarm optimization inspired by the political system to solve complex problems
Abstract The Sand Cat Swarm Optimization (SCSO) algorithm is a recently introduced
metaheuristic with balanced behavior in the exploration and exploitation phases. However, it …
metaheuristic with balanced behavior in the exploration and exploitation phases. However, it …
Chaotic sand cat swarm optimization
In this study, a new hybrid metaheuristic algorithm named Chaotic Sand Cat Swarm
Optimization (CSCSO) is proposed for constrained and complex optimization problems. This …
Optimization (CSCSO) is proposed for constrained and complex optimization problems. This …
A parallel heuristic for hybrid job shop scheduling problem considering conflict-free AGV routing
In this study, a novel and computationally efficacious Parallel Two-Step Decomposition-
Based Heuristic (PTSDBH) and a Mixed Integer Linear Programming (MILP) are developed …
Based Heuristic (PTSDBH) and a Mixed Integer Linear Programming (MILP) are developed …
Solving line balancing and AGV scheduling problems for intelligent decisions using a Genetic-Artificial bee colony algorithm
Due to the rapid advancement of technology, the demand for electronic devices in various
sectors such as consumer electronics, automotive, telecommunications, healthcare, and …
sectors such as consumer electronics, automotive, telecommunications, healthcare, and …
An augmented Lagrangian approach with general constraints to solve nonlinear models of the large-scale reliable inventory systems
Abstract The Augmented Lagrangian method (ALM) is one of the algorithms in a class of
methods for constrained optimization of nonlinear problems (NLP) that seeks a solution by …
methods for constrained optimization of nonlinear problems (NLP) that seeks a solution by …
Robust active yaw control for offshore wind farms using stochastic predictive control based on online adaptive scenario generation
Y Wang, S Wei, W Yang, Y Chai - Ocean Engineering, 2023 - Elsevier
Subject to the inherent high uncertainty of wind, the prediction for its speed and direction
may be insufficiently accurate, the resulting decision actions of active yaw control (AYC) may …
may be insufficiently accurate, the resulting decision actions of active yaw control (AYC) may …
Priority-based two-phase method for hierarchical service composition allocation in cloud manufacturing
C Tang, M Goh, S Zhao, Q Zhang - Computers & Industrial Engineering, 2024 - Elsevier
Manufacturing service composition (MSC) is an essential issue in cloud manufacturing,
which streamlines complex manufacturing tasks into manageable subtasks and integrates …
which streamlines complex manufacturing tasks into manageable subtasks and integrates …
Reactor lightweight shielding optimization method based on parallel embedded genetic particle-swarm hybrid algorithm
Reactor lightweight shielding design is a multi-objective optimization problem, which must
balance multi-dimensional design parameters such as dose, weight and volume. Combining …
balance multi-dimensional design parameters such as dose, weight and volume. Combining …