Designing Multi-Objective Optimization Model of Electricity Market Portfolio for Industrial Consumptions under Uncertainty by Saeed Khalili, Ebrahim Abbasi, Bardia Behnia, Mohammad Amirkhan

“…Due to the small number of industrial subscribers, the whole population was studied. A genetic algorithm has been used to solve this optimization problem. …”
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Evolved Motor Design Process to Reduce the Design Expense of Axial Flux Permanent Magnet Motor by Jong-Min Ahn, Dong-Kuk Lim, Min-Mo Koo

“…This paper proposes a design process that combines an initial electromagnetic design using analytical techniques with an optimal design based on a multi-objective optimization algorithm, aiming to reduce the design cost of an axial flux permanent magnet motor for urban air mobility traction. …”
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Trajectory and communication scheduling optimization for the rechargeable UAV aided data collection system by Qianwen LI, Jianfeng CHEN, Miao CUI, Guangchi ZHANG

“…A rechargeable unmanned aerial vehicle (UAV) aided wireless sensor network was considered, which consists of multiple ground terminals with a large amount of time-sensitive data to be collected.Due to the limited battery capacity, the UAV cannot collect the data from all terminals through a single flight mission, and it needs to return to the charging pile to replenish its flight energy several times during the whole mission.The optimization of the terminal scheduling, trajectory, flight speed and transmission rate for the UAV was studied to maximize the number of terminals whose data had been collected within the data lifetime limit.Due to the variable coupling and the existence of discrete binary scheduling variables, the considered optimization problem is difficult to solve.To tackle such a difficulty, an efficient algorithm was proposed based on the stochastic optimization and the feature engineering.Specifically, the flight hover communication protocol was introduced to simplify the UAV flight process.And then a terminal scheduling algorithm was innovatively proposed with the influence factor and the stochastic preference, which extracted the features that affect the service time of the UAV, optimized the weights of the features, and further simplified the optimization problem into multiple subproblems.The subproblems were then solved by using the block coordinate descent and successive convex approximation techniques.Simulation results show that the proposed optimization algorithm achieves significant performance gains over several benchmark schemes in the scenarios with different data lifetime requirements and different numbers of ground terminals.…”
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A Multiswarm Optimizer for Distributed Decision Making in Virtual Enterprise Risk Management by Yichuan Shao, Xingjia Yao, Liwei Tian, Hanning Chen

“…We develop an optimization model for risk management in a virtual enterprise environment based on a novel multiswarm particle swarm optimizer called PS2O. …”
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An Improved Constrained Multiobjective Optimization for Energy Multimodal Transport Among Clustering Islands by Xu Yang, Fuxing Zhang, Honglei Miao

“…To this end, this study proposes a novel energy optimization framework that aims to optimize the use of their different types of energy among clustering islands and improve the stability of the whole energy internet via a multilayer transportation network. …”
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Stochastic Planning of Synergetic Conventional Vehicle and UAV Delivery Operations by Konstantinos Kouretas, Konstantinos Kepaptsoglou

“…A nested genetic algorithm is initially used to solve the problem under fixed conditions. …”
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Optimization of multi-structural parameters in metamaterials based on the DGN co-simulation method. by Shangyang Jin, Fuxing Chen, Jie Bai, Bingfei Liu

“…Then the global algorithm is combined with the local algorithm to solve the problem of poor convergence of the global optimization algorithm while ensuring the optimization quality of the local optimization algorithm. …”
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A multi-faceted review of wind turbine optimization techniques: Metaheuristics and related issues by Hegazy Rezk, Abdul Ghani Olabi, Tabbi Wilberforce, Enas Taha Sayed

“…This article comprehensively reviews the current optimization state for wind energy systems and examines the use of metaheuristic optimization algorithms. …”
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Optimized Integral Super-Twisting Sliding Mode Control for Acute Leukemia Therapy by Muhammad Munir Butt, Azhar Iqbal Kashif Butt

“…This algorithm is utilized to fine-tune the controller parameters, ensuring optimal achievement of control objectives. …”
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Optimizing the lifetime of wireless sensor networks via reinforcement-learning-based routing by Wenjing Guo, Cairong Yan, Ting Lu

“…Reinforcement-learning-based routing protocol takes advantage of the intelligent algorithm of reinforcement learning to search for the optimal routing path for data transmission. …”
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Research and Experimental Verification of an Efficient Subframe Lightweighting Method Integrating SIMP Topology and Size Optimization by Jihui Zhuang, Fan Zeng

“…A topology optimization model was established using the Solid Isotropic Material with Penalization (SIMP) method and solved using the Method of Moving Asymptotes (MMA) algorithm. …”
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Multidimensional Resource Task Scheduling Based on Particle Swarm Optimization in Edge Computing by Zhonglu Zou, Zhuxin Zhai, Xin Yan, Zilin You, Liming Chen

“…The proposed approach enables the simultaneous scheduling of multiple tasks while iteratively adjusting the inertia weight and learning factors in the discrete particle swarm optimization (DPSO) algorithm. …”
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Dual-Layer Dynamic Optimization Model for Carbon-Conscious Transport Mode Allocation by Jing Gan, Dongmei Yan, Linheng Li

“…A sophisticated fusion algorithm, integrating the Dial_MSA algorithm with a genetic algorithm (GA), is developed to solve the model. …”
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Integrating Machine Learning and Multi-Objective Optimization in Biofuel Systems: A Review by Ivan P. Malashin, Dmitry A. Martysyuk, Vadim S. Tynchenko, Andrei P. Gantimurov, Vladimir A. Nelyub, Aleksei S. Borodulin

“…This review synthesizes key advancements in biofuel optimization, highlighting the use of techniques such as Artificial Neural Networks (ANN), Genetic Algorithms (GA), Non-Dominated Sorting Genetic Algorithm II (NSGA-II), and Response Surface Methodology (RSM). …”
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An Improved Large Neighborhood Search for Network-Level Airport Slot Allocation Optimization by Qiangzhe Wang, Yuanyuan Ma, Yifan Xu, Zhiyuan Shen, Dan Li

“…Validated through an extensive case study involving 4,695 requests across six hub airports, the algorithm achieves solutions within a 1.7% optimality gap while reducing computation time by up to 64%.…”
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Impact of Network Configuration on Hydraulic Constraints and Cost in the Optimization of Water Distribution Networks by Mojtaba Nedaei

“…The research focuses on designing and optimizing various WDN configurations while adhering to hydraulic constraints. …”
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Fog Service Placement Optimization: A Survey of State-of-the-Art Strategies and Techniques by Hemant Kumar Apat, Veena Goswami, Bibhudatta Sahoo, Rabindra K. Barik, Manob Jyoti Saikia

“…To solve this problem, various authors proposed different algorithms like the randomized algorithm, heuristic algorithm, meta heuristic algorithm, machine learning algorithm, and graph-based algorithm for finding the optimal placement. …”
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Optimizing statin therapy in HIV-infected patients: a review of pharmacotherapy considerations by Ramin Ansari, Hossein Khalili, Keyhan Mohammadi

“…Based on the available data, we developed a practical algorithm that clinicians can use to optimize statin therapy in PLWH. …”
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Adaptive optimization of electromyographic channels for intelligent prosthetic hands based on individual differences by Jianzhuang Zhao, Ye Tian, Yuxuan Wang, Weiye Ji, Mingchi Zhu

“…Compared to a single optimization algorithm, the proposed algorithm can adaptively optimize the electrode configuration based on individual differences while ensuring recognition effectiveness, retaining electrode channel information that significantly contributes to gesture classification recognition, and meeting the stable recognition of their motion intentions by different subjects.…”
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Decentralized Multi-Robot Navigation Based on Deep Reinforcement Learning and Trajectory Optimization by Yifei Bi, Jianing Luo, Jiwei Zhu, Junxiu Liu, Wei Li

“…Additionally, it introduces safety constraints through an artificial potential field (APF) to optimize these trajectories. Additionally, a constrained nonlinear optimization method further refines the APF-adjusted paths, resulting in the development of the GNN-RL-APF-Lagrangian algorithm. …”
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