Sigmoid-Function-Based Adaptive Pelican Optimization Algorithm for Global Optimization by A. F. S. Yussif, S. Adjei, B. E. Wilson

“… This paper introduces the Sigmoid-function-based Adaptive Pelican Optimization Algorithm (MPOA), an enhanced version of the traditional Pelican Optimization Algorithm (POA) aimed at improving the POA's performance. …”
Get full text

FHQ-RRT*: An Improved Path Planning Algorithm for Mobile Robots to Acquire High-Quality Paths Faster by Xingxiang Dong, Yujun Wang, Can Fang, Kemeng Ran, Guohui Liu

Get full text

An Improved Maximum Power Point Tracking Control Scheme for Photovoltaic Systems: Integrating Sparrow Search Algorithm-Optimized Support Vector Regression and Optimal Regulation fo... by Mingjun He, Ke Zhou, Yutao Xu, Jinsong Yu, Yangquan Qu, Xiankui Wen

“…In this study, an improved MPPT control scheme based on the technique of predicting the reference current at the MPP and regulating the optimal current is proposed. …”
Get full text

Multi-objective coordinated control and optimization for photovoltaic microgrid scheduling by Da Yu, Kai Hou, Xu Lin, Guoyang Cai, Xin Shan, Weihua Wang

“…This paper proposes a multi-objective coordinated control and optimization system for PV microgrids. To address the challenges of slow convergence and local optima in traditional PV microgrid scheduling methods, this study introduced an improved multiple objective particle swarm optimization (IMOPSO) algorithm that integrates an adaptive inertia weight adjustment strategy based on optimal similarity and a multi-directional iterative Pareto solution archive update mechanism. …”
Get full text

ＲGB-DSLAM Visual Odometry Optimization Algorithm by DONG Jing-wei, JIANG Yi-ming, HAN Zhi-yu

Get full text

Research on Day-Ahead Optimal Scheduling of Wind–PV–Thermal–Pumped Storage Based on the Improved Multi-Objective Jellyfish Search Algorithm by Yunfei Hu, Kefei Zhang, Sheng Liu, Zhong Wang

“…It is assessed using the improved multi-objective jellyfish search (IMOJS) algorithm, and its effectiveness is demonstrated through comparison with a fixed-speed pumped storage (FS-PS) system. …”
Get full text

Attack resilient IoT security framework using multi head attention based representation learning with improved white shark optimization algorithm by Jawhara Aljabri

“…This paper presents a multi-head attention-driven intrusion detection with improved white shark optimization algorithm (MHAID-IWSOA) methodology in IoT networks. …”
Get full text

A low-carbon scheduling method based on improved ant colony algorithm for underground electric transportation vehicles by Yizhe Zhang, Yinan Guo, Yao Huang, Shirong Ge

“…To solve this problem, an improved ant colony optimization algorithm integrated with Q-learning (ACO-QL) is proposed. …”
Get full text

Ship path planning based on improved multi-scale A* algorithm of collision risk function by Chunyu Song, Teer Guo, Jianghua Sui

“…Moreover, in order to improve the efficiency of optimal path planning in the context of complex sea areas while ensuring path safety, the paper proposes a collision risk function to optimize the determination of the cost of A* algorithm nodes, thereby enhancing the heuristic function of the A* algorithm. …”
Get full text

Improved ant colony algorithm based cloud computing user task scheduling algorithm by Sining LUO, Hualong WANG, Hongyu LI, Wei PENG

“…In recent years,with the development of power information,more and more power applications and tasks are deployed in the cloud.Because of the dynamic heterogeneity of cloud resources and power applications,it is a challenge in the cloud computing system to realize resource division and task scheduling.Power applications need to be able to achieve a rapid response and minimum completion time,and schedulers should consider the load of each cloud computing node to ensure the reliability of cloud computing.A task scheduling algorithm based on the algorithm of improving an ant colony was proposed to solve the problem of task scheduling in virtual machines.Through the improvement of the standard ant colony algorithm,the task scheduling time was reduced and load balancing was realized while minimizing the overall completion time.The results show that the algorithm can shorten the task scheduling time and realize the load balancing of cloud nodes,which provides technical basis for the optimization of power cloud computing.…”
Get full text

Hierarchical multi step Gray Wolf optimization algorithm for energy systems optimization by Idriss Dagal, AL-Wesabi Ibrahim, Ambe Harrison, Wulfran Fendzi Mbasso, Ahmad O. Hourani, Ievgen Zaitsev

“…Abstract Gray Wolf Optimization (GWO), inspired by the social hierarchy and cooperative hunting behavior of gray wolves, is a widely used metaheuristic algorithm for solving complex optimization problems in various domains, including engineering design, image processing, and machine learning. …”
Get full text

Optimization of power output in plateau photovoltaic power stations using a hybrid Kepler and Gaussian quantum particle swarm algorithm by Shuang Gan, Heng Hu, Shaoshuai Li, Qian Peng, Taidong Yan, Huasheng Gong, Yuancheng Zhang

“…The proposed solution integrates the Kepler Optimization Algorithm (KOA) with the Gaussian Quantum Improved Particle Swarm Optimization (GQPSO) to address multi-objective optimization, with the goal of maximizing power generation, minimizing operational costs, and enhancing system stability. …”
Get full text

Modified Ant Colony Optimization to Improve Energy Consumption of Cruiser Boundary Tour with Internet of Underwater Things by Hadeel Mohammed, Mustafa Ibrahim, Ahmed Raoof, Amjad Jaleel, Ayad Q. Al-Dujaili

“…The optimization algorithm specifies the best order in which to visit all the sensor nodes, while it also works to adjust the AUV’s information-gathering locations according to the permissible data transmission range. …”
Get full text

Joint Optimization Method for Preventive Maintenance and Train Scheduling of Subway Vehicles Based on a Spatiotemporal Network Graph by Chuanzhen Liu, Zhongwei Xu, Meng Mei, Wenqing Li

“…Finally, an improved genetic algorithm is employed to solve the model and determine the optimal scheduling and maintenance strategy. …”
Get full text

An Improved Marriage in Honey-Bee Optimization Algorithm for Minimizing Earliness/Tardiness Penalties in Single-Machine Scheduling with a Restrictive Common Due Date by Pedro Palominos, Mauricio Mazo, Guillermo Fuertes, Miguel Alfaro

“…This study evaluates the efficiency of a swarm intelligence algorithm called marriage in honey-bee optimization (MBO) in solving the single-machine weighted earliness/tardiness problem, a type of NP-hard combinatorial optimization problem. …”
Get full text

A novel TID + IDN controller tuned with coatis optimization algorithm under deregulated hybrid power system by Geetanjali Dei, Deepak Kumar Gupta, Binod Kumar Sahu, Mohit Bajaj, Vojtech Blazek, Lukas Prokop

Get full text

Improved Binary Grey Wolf Optimization Approaches for Feature Selection Optimization by Jomana Yousef Khaseeb, Arabi Keshk, Anas Youssef

“…Three improved binary Grey Wolf Optimization (GWO) approaches are proposed in this paper to optimize the feature selection process by enhancing the feature selection accuracy while selecting the least possible number of features. …”
Get full text

Solving the 3D Multi-Objective Dynamic AUV Path Planning Problem Based on the Improved Morphin-Altruistic NSGAII Algorithm by Man Zhang, Jianhong Chen, Haibin Ouyang, Shangbin Long, Steven Li, Chunliang Zhang, Weiping Ding, Essam H. Houssein

“…Dynamic path planning seeks to find an optimal path for AUVs from a start point to the target while avoiding collisions with moving obstacles. …”
Get full text

Multi-Objective Optimization of Speed Profile for Railway Catenary Maintenance Vehicle Operations Based on Improved Non-Dominated Sorting Genetic Algorithm III by Bingli Zhang, Gan Shen, Yixin Wang, Yangyang Zhang, Chengbiao Zhang, Xinyu Wang, Zhongzheng Liu, Xiang Luo

“…The implementation of pre-optimized speed profiles significantly reduces the energy consumption while improving key operational performance metrics, such as ride comfort, punctuality, and safety. …”
Get full text

A Rapid Convex Programming Method for Air-to-Air Missile Trajectory Based on Improved Trust-Region Algorithm by Zeng Yuwen, Zhang Huijun, Liao Xueyang

“…Aiming at the shortcomings of traditional guidance laws for air-to-air missiles in handling multiple nonlinear constraints during the mid-course guidance, this paper proposes an optimization method for mid-course guidance trajectory using sequential convex programming (SCP), and designs an improved trust-region algorithm to enhance the convergence performance of the optimization. …”
Get full text