A new approach for bin packing problem using knowledge reuse and improved heuristic by Jie Fang, Xubing Chen, Yunqing Rao, Yili Peng, kuan Yan

“…The classic packing solution is a hybrid algorithm based on heuristic positioning and meta-heuristic sequencing, which has the problems of complex solving rules and high time cost. …”
Get full text

Improving Data Privacy in the Internet of Things by Using Artificial Immune System, in Regard with the Internet Limitations by Marzieh Faridi Masouleh, Ali Harounabadi, Asal Sayyad

Get full text

Volt/VAr Regulation of the West Mediterranean Regional Electrical Grids Using SVC/STATCOM Devices With Neural Network Algorithms by H. Feza Carlak, Ergin Kayar

“…A load flow and short circuit analysis is performed on the designed transmission system for a number of critical scenarios. The modeled power system is optimized for the size and location of the FACTS devices by applying genetic algorithms (GAs) and particle swarm optimization (PSO) algorithms to the selected busbars of the FACTS devices, a strategy designed to significantly reduce system losses. …”
Get full text

Improved Quantum Artificial Bee Colony Algorithm-Optimized Artificial Intelligence Models for Suspended Sediment Load Predicting by Peng Wei, Wang Yu

“…To evaluate the predictive capability, the models are compared with quantum bee colony algorithm-optimized AI models (QABC-SVR and QABC-ANN), genetic algorithm-optimized AI models (GA-SVR and GA-ANN) and traditional AI models (SVR and ANN). …”
Get full text

Real-Time Optimal Control Strategy for Multienergy Complementary Microgrid System Based on Double-Layer Nondominated Sorting Genetic Algorithm by Min Mou, Yuhao Zhou, Wenguang Zheng, Zhongping Zhang, Da Lin, Dongdong Ke

“…In this paper, a typical model of energy input-output is established. This model combines with the operation control strategy suitable for multienergy complementary microgrid system, considers the operation mode and equipment characteristics of the system, and uses a double-layer nondominated sorting genetic algorithm to optimize the operation of each equipment in the multienergy complementary system in real time, so as to reduce the operation cost of the system.…”
Get full text

Revolutionizing Electric Vehicle Charging Stations with Efficient Deep Q Networks Powered by Multimodal Bioinspired Analysis for Improved Performance by Sugunakar Mamidala, Yellapragada Venkata Pavan Kumar, Rammohan Mallipeddi

“…This paper proposes a novel framework that integrates deep Q networks (DQNs) for real-time charging optimization, coupled with multimodal bioinspired algorithms like ant lion optimization (ALO) and moth flame optimization (MFO). …”
Get full text

Adaptive Grasp Pose Optimization for Robotic Arms Using Low-Cost Depth Sensors in Complex Environments by Aiguo Chen, Xuanfeng Li, Kerui Cen, Chitin Hon

“…Unlike traditional deep learning methods, which suffer from high data dependency and inefficiency with low-precision point clouds, the proposed approach uses ellipsoidal modeling to overcome these issues. The algorithm segments the target and then applies a three-stage optimization to refine the grasping path. …”
Get full text

A New Hyperparameter Tuning Framework for Regression Tasks in Deep Neural Network: Combined-Sampling Algorithm to Search the Optimized Hyperparameters by Nguyen Huu Tiep, Hae-Yong Jeong, Kyung-Doo Kim, Nguyen Xuan Mung, Nhu-Ngoc Dao, Hoai-Nam Tran, Van-Khanh Hoang, Nguyen Ngoc Anh, Mai The Vu

“…The primary goal is to improve hyperparameter tuning performance in deep learning models compared to conventional methods such as Bayesian Optimization and Random Search. …”
Get full text

Optimal Computation Offloading Decisions Based on System Utility and Cost Balance by Bingxue Zhang, Xisheng Li, Jia You

“…By calculating the full load rate of edge server clusters, we describe and evaluate the operational efficiency of the system, aiming to design a computation offloading decision scheme that not only reduces costs, but also enhances system utility. Based on the new evaluation model, an objective function is constructed to minimize the system’s cost-utility ratio, and an improved particle swarm optimization algorithm with enhanced search capabilities is proposed to solve it by designing a computation offloading strategy. …”
Get full text

Soil water content estimation by using ground penetrating radar data full waveform inversion with grey wolf optimizer algorithm by M. H. Zhang, X. Feng, M. Bano, C. Liu, Q. Liu, X. Wang

“…Full waveform inversion (FWI) can use the information of the entire waveform, which can improve the accuracy of parameter estimation. This study proposes a novel SWC estimation scheme by using the FWI of GPR, optimized by the grey wolf optimizer (GWO) algorithm. …”
Get full text

Surfactants Adsorption onto Algerian Rock Reservoir for Enhanced Oil Recovery Applications: Prediction and Optimization Using Design of Experiments, Artificial Neural Networks, and... by Kahina Imene Benramdane, Mohamed El Moundhir Hadji, Mohamed Khodja, Nadjib Drouiche, Bruno Grassl, Seif El Islam Lebouachera

“…Unlike traditional data acquisition methods, this approach enables a methodical and structured exploration of adsorption behavior while reducing the number of required experiments, leading to improved prediction accuracy, optimization, and cost-effectiveness. …”
Get full text

Chain hybrid feature selection algorithm based on improved Grey Wolf Optimization algorithm. by Xiaotong Bai, Yuefeng Zheng, Yang Lu, Yongtao Shi

“…It also shows that the algorithm improves the generalization ability and performance of the model.…”
Get full text

Application of Multi-Objective Optimization for Path Planning and Scheduling: The Edible Oil Transportation System Framework by Chin S. Chen, Chia J. Lin, Yu J. Lin, Feng C. Lin

“…The method employs the A* and Dijkstra pathfinding algorithm to determine the shortest pipeline route for each task, and estimates pipeline resource usage to derive a node cost weight function. …”
Get full text

Enhancing PM_2.5 Air Pollution Prediction Performance by Optimizing the Echo State Network (ESN) Deep Learning Model Using New Metaheuristic Algorithms by Iman Zandi, Ali Jafari, Aynaz Lotfata

“…This study evaluates efficient metaheuristic algorithms for optimizing deep learning model hyperparameters to improve the accuracy of PM_2.5 concentration predictions. …”
Get full text

Enhanced Search Spring Algorithm for Green Agri-Food Supply Chain Network Design by Xiaoya Hu

“…In light of these challenges, this study presents a new Enhanced Search Spring Algorithm (ESSA), which optimizes GASCN by minimizing total transportation costs and is characterized by improved solution quality and computational efficiency. …”
Get full text

Relaxation Parameter Optimization in Electrical-to-Mechanical Co-Simulation Based on Time Windowing WR Technique by Md Moktarul Alam, Richard Perdriau, Mohammed Ramdani, Mohsen Koohestani

“…This paper presents an innovative approach to enhancing the time windowing waveform relaxation (WR) technique in electrical-to-mechanical co-simulation by optimizing relaxation parameters for improved performance. …”
Get full text

Multi-objective DG placement in radial distribution systems using the IbI logic algorithm by Nitin Saxena, M Pandit, L Srivastava

“…This paper presents a unique optimization method based on the incomprehensible but intelligible-in-time (IbI) logic algorithm (ILA) to optimally place dispersed generators in small, medium, large, and very large (16-, 33-, 69-, and 118-bus) radial distribution power networks to reduce power losses, the total operating cost, and the voltage deviation and improve the voltage level. …”
Get full text

AquaFlowNet a machine learning based framework for real time wastewater flow management and optimization by P. Prabu, Ala Saleh Alluhaidan, Romana Aziz, Shakila Basheer

“…However, most existing methods rely on static or rule-based models, which lack the flexibility to handle fluctuating flow rates, variable environmental loads, and unforeseen disruptions. …”
Get full text

Improved Particle Swarm Optimization Algorithm Optimize the Control Strategy of Family Energy Management System by WEI Qi, LI Shi-nan, ZHU Ying-ying

“…In order to better respond accding to the demand of TOU price control project management of family family load and energy，put forward the household electricity load control strategy，based on analysis of the existing household electricity load control strategies，using improved particle swarm optimization algorithm for the control strategy optimization target，the establishment of a single-user，multi-user household electricity control optimization model，In the MATLAB platform，the results of optimization algorithm are analyzed by simulation. …”
Get full text

Multi-Objective Evolution and Swarm-Integrated Optimization of Manufacturing Processes in Simulation-Based Environments by Panagiotis D. Paraschos, Georgios Papadopoulos, Dimitrios E. Koulouriotis

“…Multiple objective functions are formulated to optimize the behavior of the system by reducing the work-in-progress items and improving both cost-effectiveness and service level. …”
Get full text