Accelerated development of multi-component alloys in discrete design space using Bayesian multi-objective optimisation by Osman Mamun, Markus Bause, Bhuiyan Shameem Mahmood Ebna Hai

“…This study evaluates several leading multiobjective BO acquisition functions–namely, parallel expected hypervolume improvement (qEHVI), noisy qEHVI, parallel parEGO, and parallel noisy parEGO (qNparEGO)–in optimizing the physical properties of multi-component alloys. …”
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Optimization of rotor-side controller parameters in doubly fed induction generators based on an improved NSGA-II. by Yanling Lv, Xiang Zhao, Zexin Mou

“…In particular, a multiobjective optimization framework based on an improved nondominated sorting genetic algorithm II (NSGA-II) is proposed by establishing a dynamic model of the rotor-side converter and investigating the operational dynamics of proportional-integral-derivative controllers under voltage transients. …”
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Dynamically Signal Timing Optimization of Isolated Intersection Traffic Lights Based on a Dual-Layer Framework by Junqi Shao, Ke Zhang, Anyou Wang, Shen Li

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Optimal Configuration of Additional Heat Source for CHP System considering Demand Response Based on Comprehensive Benefits by Yuting Zhao

“…The hierarchical sequence method solves problems sequentially based on the importance of optimization goals, ensuring the satisfaction of the configuration scheme. …”
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A PSO-Optimized Minimum Spanning Tree-Based Topology Control Scheme for Wireless Sensor Networks by Wenzhong Guo, Bin Zhang, Guolong Chen, Xiaofeng Wang, Naixue Xiong

“…In the proposed scheme, we transform the problem into a model of multicriteria degree constrained minimum spanning tree (mcd-MST) and design a nondominated discrete particle swarm optimization (NDPSO) to deal with this problem. To obtain a better approximation of true Pareto front, the multiobjective strategy with a fitness function based on niche and phenotype sharing function is applied in NDPSO. …”
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Intelligent bulk cargo terminal scheduling based on a novel chaotic-optimal thermodynamic evolutionary algorithm by Shida Liu, Qingsheng Liu, Li Wang, Xianlong Chen

“…The proposed method is adept at achieving multiobjective optimization, simultaneously improving the service level and reducing costs for bulk cargo terminals, which in turn boosts their competitiveness. …”
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Optimization of K-Shaped Metal Sealing Ring for Subsea Tubing Hanger Based on Response Surface Method by Huan Xie, Hongxia Zhang, Yiwei Fan, Liyuan Liu, Wei Zeng

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Active and Reactive Power Control for Wind Turbines Based DFIG Using LQR Controller with Optimal Gain-Scheduling by Ashraf Radaideh, Mu’men Bodoor, Ayman Al-Quraan

“…This paper proposes an optimal gain-scheduling for linear quadratic regulator (LQR) control framework to improve the performance of wind turbines based Doubly Fed Induction Generator (DFIG). …”
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Pareto Design of State Feedback Tracking Control of a Biped Robot via Multiobjective PSO in Comparison with Sigma Method and Genetic Algorithms: Modified NSGAII and MATLAB’s Toolbo... by M. J. Mahmoodabadi, M. Taherkhorsandi, A. Bagheri

“…Among the used evolutionary optimization algorithms to design the controller for biped robots, the proposed method operates better in the aspect of designing the controller since it provides ample opportunities for designers to choose the most appropriate point based upon the design criteria. …”
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A Novel Double Cluster and Principal Component Analysis-Based Optimization Method for the Orbit Design of Earth Observation Satellites by Yunfeng Dong, Xiaona Wei, Lu Tian, Fengrui Liu, Guangde Xu

“…The weighted sum and genetic algorithm-based hybrid method (WSGA-based HM), which has been applied to multiobjective orbit optimizations, is negatively influenced by human factors through the artificial choice of the weight coefficients in weighted sum method and the slow convergence of GA. …”
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Enhanced Unmanned Surface Vehicle Path Planning Based on the Pair Barracuda Swarm Optimization Algorithm: Implementation and Performance in Thousand Island Lake by Binghua Shi, Zeyu Liu, Zhou He, Chen Wang, Jia Guo

“…An enhanced path planning method for USVs based on the pair barracuda swarm optimization (PBSO) algorithm is proposed, and the complex water environment of Thousand Island Lake is taken as an example. …”
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Isolation Enhancement Based on TM010 and TE30 Mode Characteristics in a Patch Antennas Using Genetic Algorithm Optimization for Ku-Band Applications by Muddineni Raveendra, U. Saravanakumar, P. Padmaloshani, P. Saam Prasanth Dheeraj, Anand Anbalagan, R. Sreelakshmy

“…A genetic algorithm with tournament selection and a multiobjective function was applied to optimize key performance metrics, such as impedance matching, bandwidth, and gain. …”
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Optimization Management of Storage Location in Stereoscopic Warehouse by Integrating Genetic Algorithm and Particle Swarm Optimization Algorithm by Shuhong Zhang, Xianghui Zheng, Fan Xu, Suzhen Wang, Qixia Zhang, Yuan Cao

“…First, the study constructed a multiobjective mathematical model based on the weight, frequency of use, and category of the goods. …”
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Automation Countermeasure System for Intersection Optimization by Hua-pu Lu, Zhi-yuan Sun, Wen-cong Qu, Yue Li

“…To satisfy the demand of congestion problem solving in intersections, this paper studies the method of automation countermeasure system for intersection optimization (ACSIO). Taking into account the extensive contents and objectives of intersection optimization, this paper puts forward the functions and architecture of ACSIO based on intersection optimization problem statement. …”
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Duality without constraint qualification in nonsmooth optimization by S. Nobakhtian

“…We are concerned with a nonsmooth multiobjective optimization problem with inequality constraints. …”
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Parameter Design and Performance Optimization of Aerostatic Bearing by YANG Chunmei, CAO Bingzhang

“…In this paper, problems such as loadcarrying capacity, low stiffness, and vibration caused by large volume flow rate of aerostatic bearing has been studied In order to solve these problems, the particle swarm optimization algorithm is used to optimize the key parameters of throttle orifice on aerostatic bearing The simplified twodimensional Reynolds equation is solved by finite element method and the mathematical model is built Based on this model, the main performance parameters such as loadcarrying capacity, stiffness and volume flow rate of aerostatic bearing are calculated The coupling relationship between the structural dimension parameters which determining the main performance of aerostatic bearing is analyzed The multiobjective optimization design of the structural dimension parameters is carried out by particle swarm optimization With the simulation calculation of the aerostatic bearing, the loadcarrying capacity, stiffness, volume flow rate and other relevant performances are calculated The main performance of the optimized aerostatic bearing is compared with the original data The results show that compared with the performance before optimization, the loadcarrying capacity, stiffness of the aerostatic bearing are increased by 17%, 363% and the volume flow rate is decreased by 434% And the problems such as low loadcarrying capacity, low stiffness, and vibration caused by large volume flow rate of aerostatic bearing has been solved…”
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Mechanism-learning prediction model for pitting depth of buried pipeline based on HMOGWO-RF by Fulin SONG, Hong ZHAO, Xingyuan MIAO

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Bilevel Optimization for the Hazmat Transportation Problem with Lane Reservation by Shengzhong Zhang, Qianqian Hui, Xue Bai, Rongting Sun

“…Two hybrid metaheuristic algorithms based on the particle swarm optimization algorithm and the genetic algorithm, respectively, are proposed to solve the bilevel model. …”
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Illustration Design Model with Clustering Optimization Genetic Algorithm by Jing Liu, Qixing Chen, Xiaoying Tian

“…In addition, a multiobjective optimization genetic algorithm with complex constraints based on group classification is proposed. …”
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Optimizing Ontology Alignment through Improved NSGA-II by Yikun Huang, Xingsi Xue, Chao Jiang

“…Over the past decades, a large number of complex optimization problems have been widely addressed through multiobjective evolutionary algorithms (MOEAs), and the knee solutions of the Pareto front (PF) are most likely to be fitting for the decision maker (DM) without any user preferences. …”
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