-
481
Learning path planning methods based on learning path variability and ant colony optimization
Published 2024-12-01“…Subsequently, an ant colony optimization algorithm is used to generate learning paths. …”
Get full text
Article -
482
Leveraging ensemble convolutional neural networks and metaheuristic strategies for advanced kidney disease screening and classification
Published 2025-04-01“…MobileNetV2, ResNet50, and EfficientNet-B0 hyperparameters have been optimized using a modified grey wolf optimization (GWO) approach for better performance. …”
Get full text
Article -
483
A Study on Container Storage Optimization in Yards Based on a Hyper-Heuristic Algorithm with a Q-Learning Mechanism
Published 2025-06-01“…The objective is to minimize the carbon emissions and the number of container rehandling operations in ports, for which a mixed-integer linear programming model is built. Both heuristic algorithms and hyper-heuristic algorithms are employed to optimize the container storage plan, and their applicability in storage optimization is compared. …”
Get full text
Article -
484
Multi-objective optimization of design parameters for tractor hydro-mechanical continuously variable transmissions
Published 2025-04-01“…In this paper, an independently designed hydro-mechanical CVT transmission is taken as the research object, and the transmission design parameters are optimized based on the tractor’s whole life-cycle speed usage rate, and the Multi-Objective Genetic Algorithm(MOGA) is used for optimization and solution. …”
Get full text
Article -
485
Application of evolutionary algorithm in estimation of environmental performance in farm systems
Published 2019-12-01“…The outcomes of the present study showed the valuable application of multi-objective genetic algorithm for optimization of energy consumption in wheat cultivation.…”
Get full text
Article -
486
Autonomous Decision-Making for Air Gaming Based on Position Weight-Based Particle Swarm Optimization Algorithm
Published 2024-12-01“…To verify the effectiveness of the optimization, a 6v6 aircraft gaming simulation example is provided for comparison, and the experimental results show that the convergence speed of the optimized PW-PSO algorithm is 56.34% higher than that of the traditional PSO; therefore, the algorithm can improve the speed of decision-making while meeting the performance requirements.…”
Get full text
Article -
487
Event-Triggered Discrete-Time Distributed Consensus Optimization over Time-Varying Graphs
Published 2017-01-01“…Under the assumption that the network topology is uniformly strongly connected and weight-balanced, the novel event-triggered distributed subgradient algorithm is capable of steering the whole network of agents asymptotically converging to an optimal solution of the convex optimization problem. …”
Get full text
Article -
488
-
489
Tramp Ship Routing and Scheduling with Integrated Carbon Intensity Indicator (CII) Optimization
Published 2025-04-01“…The Gale–Shapley algorithm is employed to achieve stable vessel–cargo matching, and the genetic algorithm is adopted for iterative optimization. …”
Get full text
Article -
490
Value chain optimization in large scale gas network considering elevation and transmission direction
Published 2025-07-01“…The company determines the quantity of gas purchased or extracted from various gas sources and transmits them to demand nodes across the network by controlling the pressure levels of the compression stations. The whole process is the major value chain of the company. …”
Get full text
Article -
491
An improved dung beetle optimizer based on Padé approximation strategy for global optimization and feature selection
Published 2025-03-01“…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
Article -
492
Enhancing Diversity and Convergence in MMOPs with a Gaussian Similarity-Based Evolutionary Algorithm
Published 2025-01-01“…We introduce a mechanism that balances diversity in both the decision and objective spaces, aiming to enhance diversity while maintaining convergence in both spaces. We propose a multi-modal multi-objective evolutionary algorithm (MMEA) that selects qualified solutions based on Gaussian similarity. …”
Get full text
Article -
493
Developing an Optimization Model for Minimizing Solid Waste Collection Costs
Published 2023-12-01“…The Simulated Annealing (SA) algorithm, one of the heuristic optimization techniques used to identify the best solutions to complicated problems, is employed to solve the routing problem of solid waste collection vehicles in this study. …”
Get full text
Article -
494
Particle Swarm Optimization Based Optimal Design of Six-Phase Induction Motor for Electric Propulsion of Submarines
Published 2022-04-01“…This research presented a comparison of optimal model design of a six phase squirrel cage induction motor (IM) for electric propulsion by using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). …”
Get full text
Article -
495
An improved multiple adaptive neuro fuzzy inference system based on genetic algorithm for energy management system of island microgrid
Published 2025-05-01“…The prediction system is implemented by using 8760 samples based on an hourly meteorological data of a whole year. GA is used as an optimization technique for training MANFIS to accomplish the desired objects of EMS. …”
Get full text
Article -
496
Parameter Optimization of Milling Process for Surface Roughness Constraints
Published 2023-02-01“… In the milling process of 6061 aluminum considering the requirement of controlling the surface roughness of workpiece, artificially selected milling parameters may be conservative, resulting in low material removal rate and high manufacturing cost.Taking the surface roughness as the constraint condition and the maximum material removal rate as the goal, the surface roughness regression model is established based on extreme gradient boosting (XGBOOST) with the spindle speed, feed speed and cutting depth as the optimization objects.The milling parameters of spindle speed, feed speed and cutting depth are optimized by genetic algorithm.The optimal milling parameters are obtained by using the multi objective optimization characteristics of genetic algorithm.It can be seen from the four groups of optimization results that the maximum change of surface roughness is only 0.048μm, while the minimum material removal rate increases by 2458.048mm3/min.While achieving surface roughness, the processing efficiency is improved, and the manufacturing costs are reduced, resulting in good optimization effects, which has a certain guiding role in the actual processing.…”
Get full text
Article -
497
Research on 3D Path Optimization for an Inspection Micro-Robot in Oil-Immersed Transformers Based on a Hybrid Algorithm
Published 2025-04-01“…Once the optimal node sequence is determined, detailed path planning between adjacent points is executed through a synergistic combination of the A algorithm*, Rapidly exploring Random Tree (RRT), and Particle Swarm Optimization (PSO). …”
Get full text
Article -
498
Reflective Distributed Denial of Service Detection: A Novel Model Utilizing Binary Particle Swarm Optimization—Simulated Annealing for Feature Selection and Gray Wolf Optimization-...
Published 2024-09-01“…The BPSO-SA algorithm enhances the global search capability of Particle Swarm Optimization (PSO) using the SA mechanism and effectively screens out the optimal feature subset; the GWO algorithm optimizes the hyperparameters of LightGBM by simulating the group hunting behavior of gray wolves to enhance the detection performance of the model. …”
Get full text
Article -
499
-
500
An Enhanced Artificial Lemming Algorithm and Its Application in UAV Path Planning
Published 2025-06-01“…When applied to UAV path planning in large- and medium-scale environments with realistic obstacle constraints, the EALA generates Pareto-optimal paths that minimize length, curvature, and computation time while guaranteeing collision avoidance. …”
Get full text
Article