A Multi-Objective Optimization Study on a Certain Lecture Hall Based on Thermal and Visual Comfort by Hui Xi, Shichao Guo, Wanjun Hou, Bo Wang

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Enhanced mask R-CNN for luminaire detection through brightness balancing and distribution-guided optimization in tunnels by Xiaoqiong Qin, Bintao Xu, Chenchen Wang, Lirui Liu, Linfu Xie, Rong Liu, Mingwei Hu, Xiangsheng Chen

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Maximum Torque per Ampere Control of PMSMs Using Real-Time Numerical Optimization by Yong Xu, Min-Yi Lin, Wen-Jie Wan, Yunchong Wang, Jian-Xin Shen

“…It is evaluated alongside the Levenberg-Marquardt algorithm (LMA), which is renowned for its high accuracy and rapid convergence. …”
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Estimating the transpiration of kiwifruit using an optimized canopy resistance model based on the synthesis of sunlit and shaded leaves by Zongyang Li, Lu Zhao, Zhengxin Zhao, Huanjie Cai, Liwen Xing, Ningbo Cui

“…This study established a rc estimation model based on a synthesis of sunlit and shaded leaves (SSL) and optimized it using Ant Colony Optimization (ACO), Grey Wolf Optimizer (GWO), and Whale Optimization Algorithm (WOA). …”
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Optimizing Route Planning via the Weighted Sum Method and Multi-Criteria Decision-Making by Guanquan Zhu, Minyi Ye, Xinqi Yu, Junhao Liu, Mingju Wang, Zihang Luo, Haomin Liang, Yubin Zhong

“…Secondly, this study compares seven heuristic algorithms—the genetic algorithm (GA), particle swarm optimization (PSO), the tabu search (TS), genetic-particle swarm optimization (GA-PSO), the gray wolf optimizer (GWO), and ant colony optimization (ACO)—to solve the TOPSIS model, with GA-PSO performing the best. …”
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Mcaaco: a multi-objective strategy heuristic search algorithm for solving capacitated vehicle routing problems by Yanling Chen, Jingyi Wei, Tao Luo, Jie Zhou

“…Through a series of experiments, it is demonstrated that compared to multi-objective particle swarm optimization (MOPSO), non-dominated sorting genetic algorithm II (NSGA-II), and multi-objective sparrow search algorithm (MOSSA), the proposed MCAACO significantly reduces travel paths by an average of 3.05% and increases vehicle service coverage by an average of 3.2%, while satisfying vehicle capacity constraints. …”
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SOE: A Multi-Objective Traffic Scheduling Engine for DDoS Mitigation with Isolation-Aware Optimization by Mingwei Zhou, Xian Mu, Yanyan Liang

“…These objectives are combined into a composite scalarized loss function with soft constraints, prioritizing a BTAR while maintaining flexibility. To solve this problem, we introduce MOFATA, a multi-objective extension of the Fata Morgana Algorithm (FATA) within a Pareto-based evolutionary framework. …”
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Research on temporary shipping network model and optimization strategy under partial shipping network disruption by Zhiyi Ye, Xiang Yuan

“…To solve this NP-hard problem, custom operators for meta-heuristic algorithms (SA, GA and PSO) are designed and enhanced through Bayesian hyperparameter optimization, ensuring algorithmic adaptability to real-time disruptions. …”
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Modeling Energy Communities: A Case Study of Quantum Approximate Optimization on a Superconducting Processor by Mateo Alonso, Guillermo Rubinos Rodriguez, Pablo Diez-Valle, Ana Garbayo, Xela Garcia-Santiago, Gonzalo Blazquez Gil

“…This work explores the use of variational quantum algorithms to optimize energy distribution among users in energy communities, using real data from a community lab. …”
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Computer-Aided Efficient Routing and Reliable Protocol Optimization for Autonomous Vehicle Communication Networks by Alaa Kamal Yousif Dafhalla, Mohamed Elshaikh Elobaid, Amira Elsir Tayfour Ahmed, Ameni Filali, Nada Mohamed Osman SidAhmed, Tahani A. Attia, Badria Abaker Ibrahim Mohajir, Jawaher Suliman Altamimi, Tijjani Adam

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Multiobjective optimization of suspension bridges via coupled modeling and dual population multiobjective particle swarm optimization by Peiling Yang, Jianhua Deng, Anli Wang

“…This study proposes a multi-objective particle swarm optimization algorithm based on a dual-population coevolution strategy (DPMOPSO) to solve the optimization problem. …”
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Parameter Optimization of a Bi-copter Type Unmanned Aerial Vehicle to Avoid Propeller-induced Vibrations During Hovering by Mehmet Kursat Yalcın, İlyas Kacar, Halil Bahadır Akyıldız

“…The double electric ducted fan loads, which transmit excitations to the fuselage, are predicted and compared using optimization methods. While the minimum vibration amplitude for stress will be achieved at 7.69 Hz, it will be 9.80 Hz. for minimum deformation without sacrificing safety factor requirement. …”
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Hierarchical Deep Learning Model Optimization Using Enhanced Evolutionary-based Approach for Fake News Detection by Deepti Nikumbh, Anuradha Thakare

“…This work introduces the Deep Learning Model with Evolutionary Computing Approach (DLECA), a novel method for compressing and optimizing hierarchical deep learning models (HDLM). …”
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Improving detection of Parkinson’s disease with acoustic feature optimization using particle swarm optimization and machine learning by Elmoundher Hadjaidji, Mohamed Cherif Amara Korba, Khaled Khelil

“…This study aims to refine PD detection systems by introducing customized weighting to acoustic features, adjusting their significance based on their correlation with the disease and the classification algorithm utilized. The particle swarm optimization algorithm is employed for this purpose, with the Oxford PD dataset serving as the source data for training and validation. …”
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Grid-connected PV inverter system control optimization using Grey Wolf optimized PID controller by Monika Gupta, P. M. Tiwari, R. K. Viral, Ashish Shrivastava, Basem Abu Zneid, Iryna Hunko

“…Abstract This paper introduces a robust and adaptive control framework that integrates a Proportional–Integral–Derivative (PID) controller with the bio-inspired Grey Wolf Optimization (GWO) algorithm for real-time tuning of controller parameters in grid-connected photovoltaic (PV) inverter systems. …”
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Multi-Parameter Optimization Using Metaheuristic Algorithms to Improve Uncrewed Aerial Vehicles’ Wireless Communications: A Performance Analysis by Lalan J. Mishra, Naima Kaabouch

“…On average, in Approach 1, the whale optimization algorithm had the shortest convergence time, while ant colony optimization was the slowest. …”
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Design and prototyping of a magnetically and hydrodynamically suspended blood pump via multiobjective optimization by Reza Sahebi-Kuzeh Kanan, Hanieh Niroomand-Oscuii, Habib Badri Ghavifekr, Farzan Ghalichi

“…In this study, a bespoke motorpump system was designed, and by optimizing the impeller geometry across fifteen design parameters, hydraulic efficiency was enhanced while hemolysis risk was reduced. …”
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Carbon Dioxide Storage Site Location and Transport Assignment Optimization for Sustainable Maritime Transport by Yanmeng Tao, Ying Yang, Yuquan Du, Shuaian Wang

“…To enhance practical applicability, a two-stage planning framework is proposed, where the first stage selects storage sites, and the second employs a genetic algorithm (GA) for transport assignment. The GA-based solution achieves a total cost only 2.4% higher than the exact MIP model while reducing computational time by 57.9%. …”
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Multi-objective Optimal Scheduling of Water-Carbon in Cascade Reservoirs during Impoundment for Carbon Emission Reduction by ZHOU Yan-lai, NING Zhi-hao, HE Jun-tao

“…[Conclusions] This study develops a multi-objective scheduling model for cascade reservoirs during the impoundment period and analyzes the nonlinear synergy and competitive relationships between carbon emissions and traditional water resource utilization benefits. The NSGA-Ⅱ optimization solutions significantly improv the long-term average power generation and storage rate while reducing greenhouse gas emissions without compromising flood control standards. …”
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UWB Base Station Deployment Optimization Method Considering NLOS Effects Based on Levy Flight-Improved Particle Swarm Optimizer by Shengliang Wang, Ming Gao, Ling’ai Li, Dong Lv, Yingqi Li

“…In this paper, we propose a new UWB BS deployment optimization method that takes into account the influence of NLOS occlusion, determines the BS deployment range and occlusion by indoor map information, uses the locatable points coverage rate in the whole indoor positioning area as the fitness function, and proposes an improved particle swarm optimization algorithm based on the Levy flight strategy (LPSO) to solve the optimization problem. …”
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