Optimizing transient gas network control for challenging real-world instances using MIP-based heuristics by Hennings, Felix, Hoppmann-Baum, Kai, Zittel, Janina

“…In this paper, we present the latest improvements of our ongoing work to tackle this problem for real-world, large-scale problem instances: By adjusting our mixed-integer non-linear programming model regarding the gas compression capabilities in the network, we reflect the technical limits of the underlying units more accurately while maintaining a similar overall model size. In addition, we introduce a new algorithmic approach that is based on splitting the complexity of the problem by first finding assignments for discrete variables and then determining the continuous variables as locally optimal solution of the corresponding non-linear program. …”
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Structural Parameter Optimization of a Tomato Robotic Harvesting Arm: Considering Collision-Free Operation Requirements by Chuanlang Peng, Qingchun Feng, Zhengwei Guo, Yuhang Ma, Yajun Li, Yifan Zhang, Liangzheng Gao

“…The compactness of the arm and the accessibility of the harvesting space serve as the optimization objectives. The Non-dominated Sorting Genetic Algorithm II (NSGA-II) multi-objective genetic algorithm is employed to optimize the arm length, and the results were validated through a virtual experiment using workspace traversal. …”
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Multi-Objective Optimization of the Rotary Turning of Hardened Mold Steel for Energy Saving and Surface Roughness Improvements by Tat Khoa Doan, Trung Thanh Nguyen, An-Le Van

“…The entropy method and vibration and communication particle swarm optimization (VCPSO) algorithm were employed to compute the weights and determine optimal factors. …”
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Cross-Domain Edge Computing Offloading Strategy for Delay-Optimized in Low Earth Orbit Satellite Network by YANG Guisong, HUANG Yechao, HE Xingyu

“…To address these challenges, an edge computing offloading process based on control domain partitioning is designed, and a latency-optimized cross-domain computing offloading strategy using the Actor-Critic algorithm is proposed. …”
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Thermo-hydrodynamic and exergy optimization of a photovoltaic thermal (PV/T) air collector using NSGA-II by Seyed Morteza Javadpour, Rasoul Soufi Noughabi, Ebrahim Kadivar

“…The Non-Dominated Sorting Genetic Algorithm (NSGA-II) optimization method, combined with the finite volume method, is employed to identify and analyze the optimal configuration in comparison to the initial design. …”
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Numerical Optimization of Laser Powder Bed Fusion Process Parameters for High-Precision Manufacturing of Pure Molybdenum by İnayet Burcu Toprak, Nafel Dogdu, Metin Uymaz Salamci

“…Optimization of process parameters is performed using FLOW-3D Release 7 software in conjunction with the HEEDS-SHERPA algorithm. …”
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An Optimization Coverage Strategy for Wireless Sensor Network Nodes Based on Path Loss and False Alarm Probability by Jianing Guo, Yunshan Sun, Ting Liu, Yanqin Li, Teng Fei

“…Based on this perception model, the optimization objective function of the WSN node optimization coverage problem is established, and then the intelligent optimization algorithm is used to solve the objective function and finally achieve the optimization coverage of sensor nodes. …”
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Multi-Objective Optimization of UAV Relay Deployment for Air-to-Ground Communications via Distributed Collaborative Beamforming by Yang Yang, Xin Feng, Jing Zhang, Hongwei Yang, Tingting Zheng

“…The MOP aims to minimize the maximum sidelobe level (SLL) and propulsion energy consumption while maximizing the transmission rate. We propose an enhanced multi-objective evolutionary algorithm, BSINSGA-II, which integrates beetle swarm optimization (BSO) into the non-dominated sorting genetic algorithm II (NSGA-II). …”
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On the Convergence of Maximum Likelihood Expectation–maximization Algorithm for Iterative Tomographic Reconstruction and the Role of Spatial Frequency, Location, Pixel Intensity, C... by Mohsen Qutbi

“…Background: It is desirable to iterate the maximum likelihood expectation–maximization (MLEM) algorithm to the point of convergence to obtain the optimal result. …”
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A novel method for simulating dynamic facades to analysing, and optimizing daylight and visual comfort in office buildings by Mehran Shahmoradi, Mansour Yeganeh

“…First, a genetic algorithm optimized 63 h of a year separately. Then, the shading device's optimum (state of a shading device that leads to gaining high indoor illumination while controlling glare level) position for all sample hours was collected. …”
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Optimal Control Scheme of Electric Vehicle Charging Using Combined Model of XGBoost and Cumulative Prospect Theory by Youseok Lim, Sungwoo Bae, Jun Moon

“…Using the predicted results, we applied the CPT algorithm to analyze the optimal operational scenarios and assess the expected profit and loss for the power grid. …”
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Optimal Utilization of Ports’ Free-of-Charge Times in One Distribution Center and Multiple Ports Inventory Systems by Zhengyi Li

“…Focusing on stationary and integer-ratio policies, we formulate this inventory management problem as an optimization problem with a convex objective function and a set of integer-ratio constraints and present O(Nlog⁡N) time algorithm to solve the relaxed problem (relaxing the integer-ratio constraints) to optimality, where N is the number of the retailers. …”
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Optimal Fault Tolerant Control of Large-Scale Wind Turbines in the Case of the Pitch Actuator Partial Faults by Younes Ait El Maati, Lhoussain El Bahir

“…The aim is to choose a small fault estimation response time while keeping a weak correlation between the tracking error and the wind turbulence noise. …”
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Comparative Evaluation of Reinforcement Learning Algorithms for Multi-Agent Unmanned Aerial Vehicle Path Planning in 2D and 3D Environments by Mirza Aqib Ali, Adnan Maqsood, Usama Athar, Hasan Raza Khanzada

“…Our findings reveal significant performance differences between the algorithms across multiple dimensions. DDPG consistently demonstrated superior reward optimization and collision avoidance performance, while PPO and MADDPG excelled in the execution time required to reach the goal. …”
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Energy saving and low carbon oriented renovation framework for educational buildings with Tianjin University case study by Xinge Du, Xiang Liu, Feng Gao, Zhihua Zhou

“…This study proposes a data-driven workflow that combines a genetic algorithm with a Bayesian optimization-based XGBoost model to optimize the retrofit design of educational buildings. …”
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Study of the Fatigue Life and Weight Optimization of an Automobile Aluminium Alloy Part under Random Road Excitation by A. Saoudi, M. Bouazara, D. Marceau

“…We present our algorithm developed to optimize the weight of an aluminium alloy sample relative to its fatigue life. …”
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Hierarchical predictive optimal control for range extension of EV with ANN based torque control for IPMSM drives by Lekshmi S, Lal Priya P S

“…The approach involves a hierarchical control scheme that integrates a model predictive controller with a torque vectoring algorithm to optimize torque demand and accurately anticipate road-specific torque requirements. …”
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Two-layer Optimization Scheduling for Off-grid Microgrids Based on Multi-agent Deep Policy Gradient by Huicong FAN, Zhiguo DUAN, Zhiyong CHEN, Shijia ZHU, Hang LIU, Wenxiao LI, Yang YANG

“…The lower-level model optimizes slow-regulating discrete devices based on mixed-integer second-order cone programming, while the upper-level model optimizes fast-regulating continuous devices using a multi-agent deep policy gradient algorithm. …”
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Development and Optimization of a Novel Semi-Submersible Floater for Floating Wind Turbines in the South China Sea by Yiming Zhong, Wenze Liu, Wei Shi, Xin Li, Shuaishuai Wang, Constantine Michailides

“…Using a differential evolution algorithm, the optimization process adjusts column diameter and spacing while considering motion response and steel usage constraints. …”
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Sentence Embedding Generation Framework Based on Kullback–Leibler Divergence Optimization and RoBERTa Knowledge Distillation by Jin Han, Liang Yang

“…First, a sentence embedding generation method based on Kullback–Leibler Divergence (KLD) optimization is proposed, which enhances semantic differentiation between sentence vectors, thereby improving the accuracy of textual similarity computation. …”
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