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multiobjective optimization Study of Stacked BGA Solder Joints Under Coupled Bending-Vibration Load and Crosstalk Effects

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IEEE TRANSACTIONS ON COMPONENTS PACKAGING AND MANUFACTURING TECHNOLOGY 2025年第3期15卷 591-602页

作者： Wu, Liye Huang, Chunyue Wei, Jisheng Liang, Ying Gao, Chao Liu, Xianjia Cao, Zhiqin Guilin Univ Elect Technol Sch Mech & Elect Engn Guilin 541004 Peoples R China Chengdu Aeronaut Vocat & Tech Coll Sch Elect & Informat Engn Chengdu 610021 Peoples R China Sichuan Prov Engn Technol Res Ctr Vanadium & Titan Panzhihua 617000 Peoples R China

A finite-element analysis model and a crosstalk analysis simulation model of stacked ball grid array package (BGA) solder joint interconnection structure were established, and the stress-strain finite-element analysis under bending-random vibration-coupled loading conditions and the crosstalk analysis between stacked BGA solder joints under high-frequency conditions were conducted, along with the completion of the bending vibration-coupled strain measurement experiment. Based on the response surface method, a multiobjective optimization mathematical model of stacked BGA solder joints was constructed, and the structural parameters were optimized using the multiobjective evolutionary algorithm based on decomposition (MOEA/D) combined with the entropy weight TOPSIS decision method. The results show that the maximum bending vibration-coupled stress and strain of the stacked BGA solder joints are both located on the lower surface of the contact between the lower solder joint and the printed circuit board (PCB) and on the outer edge of the contact surface. As the signal frequency increases, near-end crosstalk and far-end crosstalk gradually increase, and near-end crosstalk is greater than far-end crosstalk. Among the 17 sets of Pareto optimal solutions obtained, the comprehensive optimization ratios of the structure parameter combinations in the first two orders reached 9.56% and 9.63%, respectively, with the optimization effects of each target relatively average, achieving the purpose of multiobjective optimization.

关键词： Soldering Vibrations Stress Strain Loading Finite element analysis Bending Reliability Load modeling Crosstalk Bending vibration coupling crosstalk analysis entropy weight TOPSIS decision making multiobjective optimization stacked solder joints

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multiobjective optimization of perforation design with mechanism learning to increase the stimulated reservoir volume of unconventional reservoirs

GEOENERGY SCIENCE AND ENGINEERING

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GEOENERGY SCIENCE AND ENGINEERING 2025年 246卷

作者： Zhang, Yu Zeng, Fanhui Guo, Jianchun Hu, Dagan Bai, Xiaosong Gong, Gaobin Cheng, Zhangxin Southwest Petr Univ State Key Lab Oil & Gas Reservoir Geol & Exploitat Chengdu 610500 Peoples R China Univ Calgary Dept Chem & Petr Engn Calgary AB T2N 1N4 Canada

The stimulated reservoir volume (SRV) formed by multifracture (multiperforation) fracturing significantly improves the development effect of unconventional reservoirs. However, previous studies have generally overlooked differences in the SRV resulting from competitive flow among fractures in heterogeneous reservoirs, the poor interpretability of surrogate models, and the lack of rapid optimization methods. Therefore, a surrogate algorithm considering the physical constraints of reservoir heterogeneity, multifracture stress interference, and flow competitive conservation is utilized to establish an enhanced model for mechanism-learning multifracture propagation. The distance metric, performance evaluation index, objective decomposition, and objectives of uniform fracture length (UFL), moderate reconstruction bandwidth (MRB) and maximize SRV are introduced to establish a multiobjective optimization algorithm with mechanism learning. The proposed model is verified through comparison with theoretical models and monitoring results. The integrated surrogate algorithm with with physical constraints quickly and accurately performs well in surrogate fracture propagation mechanismlearning simulations. The SRV can be further enhanced by inverted generational distance evaluation to simultaneously achieve a UFL and MRB. More perforations in areas with a low permeability and high stress and a low fracturing fluid viscosity and high injection flow rate can significantly enhance the SRV. This study provides a new method for efficiently developing unconventional reservoirs.

关键词： Unconventional reservoirs Heterogeneity Enhanced model for mechanism learning multiobjective optimization Perforation design Stimulated reservoir volume

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multiobjective optimization of Class-F Oscillators

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IEEE TRANSACTIONS ON VERY LARGE SCALE INTEGRATION (VLSI) SYSTEMS 2025年第2期33卷 303-314页

作者： Qu, Zhan Chen, Zhenjiao Shi, Xingqiang Zhao, Ya Zhang, Guohe Liang, Feng Xi An Jiao Tong Univ Sch Microelect Xian 710049 Peoples R China Northwestern Polytech Univ Sch Elect & Informat Xian 710049 Peoples R China China Elect Technol Grp Corp Res Inst 58 Wuxi 214035 Peoples R China

To address the complex nonlinear problem of determining class-F voltage-controlled oscillator (VCO) dimensions, this article introduces an electronic design automation (EDA) framework that rapidly optimizes multiple design objectives yielding superior outcomes. The framework incorporates fast frequency determination, harmonic alignment, and extremal optimization of multiobjective particle swarm optimization with crowding distance (FHE-MOPSO-CD), an efficient algorithm we developed specifically for class-F VCOs, which includes transformer-based tank circuit strategies and extremum optimization techniques. Using a 55-nm CMOS process, this algorithm optimized various class-F VCO topologies, achieving excellent metrics and confirming its versatility. optimization results indicate that at a 10-MHz offset, the figure of merit (FoM) is at least 8.81 dBc/Hz higher than values reported in the literature. Compared with other analog/RF dimension optimization methods, our approach yielded a higher hypervolume, indicating better convergence and greater diversity of solutions.

关键词： optimization Voltage-controlled oscillators Oscillators Phase noise Harmonic analysis Transformers Power harmonic filters Dominant sorting electronic design automation (EDA) multiobjective optimization transformer-based tank voltage-controlled oscillator (VCO)

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multiobjective optimization in Logic Synthesis Based on TB-RM Dual Logic

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IEEE TRANSACTIONS ON COMPUTER-AIDED DESIGN OF INTEGRATED CIRCUITS AND SYSTEMS 2025年第4期44卷 1380-1393页

作者： Zhou, Yuhao Wang, Zhen Kong, Xiangxue Pan, Hongyang He, Zhenxue Zhang, Ying Jiang, Jianhui Xiao, Limin Wang, Xiang Tongji Univ Sch Comp Sci & Technol Shanghai 201804 Peoples R China Shanghai Univ Elect Power Sch Comp Sci & Technol Shanghai 200090 Peoples R China 40 Middle Sch Linyi Math Dept Middle Sch Linyi 276017 Peoples R China Fudan Univ Sch Microelect State Key Lab Integrated Chips & Syst Shanghai 200433 Peoples R China Hebei Agr Univ Key Lab Agr Big Data Hebei Prov Baoding 071001 Peoples R China Sanda Univ Sch Informat Sci & Technol Shanghai 201209 Peoples R China Beihang Univ Sch Comp Sci & Engn Beijing 100191 Peoples R China Beihang Univ Sch Elect & Informat Engn Beijing 100191 Peoples R China

Traditional logic synthesis methods are based on Boolean logic, which tends to produce redundant logic structures in dense circuit applications, such as complex number operations and error detection/correction coding. Traditional Boolean and Reed-Muller (TB-RM) logic synthesis method combining traditional Boolean (TB) logic and Reed-Muller (RM) logic can improve comprehensive optimization indexes and reduce cost. The existing TB design method is not effective when dealing with constrained systems with high-resource utilization requirements. In addition, traditional synthesis methods do not consider multiobjective optimization of area, power consumption and reliability. To solve these problems, we propose an effective dual logic synthesis method (EDSM), which includes dual logic detection method (DDM) and differential evolution algorithm based on multidimensional mutation strategy (DE-MMS). DDM can complete the logic detection function, and DE-MMS can further optimize the polarity. In addition, to evaluate the soft errors occurring more efficiently at the logic level, we propose a soft error rate (SER) estimation model. Experimental results show that compared with state-of-the-art evolutionary algorithms, EDSM can search for optimal solutions in all optimization problems;compared with commonly used TB-based minimization methods, EDSM has obvious advantages in multiobjective optimization of area, power consumption and SER. After 6-LUT FPGA technology and standard cells mapping, by selecting area as the optimal cost implementation, we obtain average improvements in the area of 14% and 2%, respectively.

关键词： Logic optimization Power demand Reliability Integrated circuit reliability Circuit faults Logic functions Logic circuits Input variables Logic gates Differential evolution algorithm logic detection logic synthesis method multiobjective optimization soft error rate (SER)

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multiobjective optimization of Mobile Coplanar Array Capacitance Sensor for Imaging Internal Damages in Asphalt Mixtures

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IEEE SENSORS JOURNAL 2025年第1期25卷 1516-1526页

作者： Shi, Bin Wang, Xiang Chen, Xueqin Yao, Kang Hu, Xing Dong, Qiao Southeast Univ Rd Engn Dept Nanjing 211189 Peoples R China Nanjing Univ Sci & Technol Civil Engn Dept Nanjing 210094 Peoples R China

Coplanar capacitance imaging technology (CCIT) is advanced in detecting and identifying internal damages in measured objects. However, typical coplanar array capacitance sensors (CACSs) exhibit contradictory performances in terms of signal strength, imaging accuracy, and detected depth. Currently, there is few CACS capable of identifying internal damage in asphalt layers accurately. To address this gap, a novel mobile CACS (MCACS) is proposed and optimized using response surface methodology (RSM) combined with a nondominated sorting genetic algorithm III optimization (NSGA-III) algorithm to image internal damages in asphalt mixtures. Initially, a central-composite design (CCD) of RSM is used to develop the statistical models of the three optimized performances of MCACS. The significance of structure parameters on the three sensor performances is then analyzed using ANOVA and 3-D response surface diagrams. Furthermore, the NSGA-III algorithm is used to optimize the multiperformances of MCACS. In addition, the optimized performances of the MCACS are validated using laboratory experiments. All three statistical models are determined to be significant since the R-squared is greater than 0.95. All of the single structure parameters are significant for the three sensor performances. Based on the optimization of the NSGA-III algorithm, the optimal solutions are predicted and confirmed with less than 5% error from the simulation results. Compared to the traditional CACS, the MCACS can identify internal damage in asphalt mixtures with optimal signal strength, uniformity of sensitivity field distribution, and penetration depth more accurately.

关键词： Capacitance Sensors Electrodes Sensor arrays Imaging Capacitive sensors Capacitance measurement Asphalt Accuracy Sensitivity Asphalt mixtures internal damage detection mobile coplanar array capacitance sensor (MCACS) multiobjective optimization response surface methodology (RSM)

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multiobjective optimization With Hybrid 2-D Equivalent Model on Axial Flux Permanent Magnet Machine for Special Electric Vehicles

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IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION 2025年第2期11卷 5819-5830页

作者： Wang, Chen Li, Kai Liu, Yunpeng Huang, Jian Zhang, Zhuoran Anhui Polytech Univ Dept Elect Engn Wuhu 241000 Peoples R China Nanjing Univ Aeronaut & Astronaut Dept Elect Engn Nanjing 210016 Peoples R China

This article proposes a new high-efficiency multiobjective optimization method for an axial flux permanent magnet (AFPM) machine. First, based on the torque production theory, a high-precision 2-D equivalent model for the AFPM machine is proposed, which can improve the accuracy of the traditional 2-D equivalent model and reduce the computation cost of the optimization design stage. Then, the hierarchical optimization strategy is proposed based on the single-parameter scanning (SPS) method and surrogate model, which improves the optimization efficiency. In addition, an improved gray wolf optimization (IGWO) algorithm is employed by integrating Tent chaotic mapping, nonlinear control parameters, and Levy flight, which enhances the global search capabilities and convergence rate. Afterward, the electromagnetic performances of the initial and optimal models are compared and analyzed based on the 3-D model and the proposed 2-D equivalent model. Finally, a 25-kW prototype is manufactured and tested to verify the effectiveness of the hybrid 2-D equivalent model and the proposed multiobjective optimization method.

关键词： Solid modeling Torque Iron Computational modeling Analytical models Atmospheric modeling optimization methods Mathematical models Accuracy Costs Axial flux permanent magnet (AFPM) machine hybrid 2-D equivalent model improved gray wolf optimization (IGWO) algorithm multiobjective optimization response surface method

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multiobjective optimization of Key Parameters for the Chamber of Low-Voltage DC Circuit Breakers Based on MHD

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IEEE TRANSACTIONS ON PLASMA SCIENCE 2025年第1期53卷 88-98页

作者： Lin, Jingyi Wu, Jianwen Xia, Shangwen Chen, Ruang Ma, Mingshun Beihang Univ Sch Automat Sci & Elect Engn Beijing 100191 Peoples R China

The extinguishing performance of low-voltage dc circuit breakers is intricately influenced by the arc motion process, which in turn is shaped by the structure of the arc chamber. Consequently, optimizing and refining the arc chamber structure is imperative for augmenting arc-extinguishing efficacy. Addressing this necessity, this study presents an advanced multiobjective optimization algorithm grounded in the magnetohydrodynamic (MHD) model for low-voltage dc circuit breakers. The optimization targets key geometrical parameters within the chamber, encompassing the arc runner length, splitter plate inclination angle, as well as the horizontal and vertical spacing between neighboring splitter plates, to minimize both arc energy and overvoltage. Relative coefficients for primary and secondary objectives are seamlessly integrated into the optimization process to bolster computational efficiency. Leveraging simulation models, this algorithm expeditiously explores the impact of various arc chamber structural parameters on arc motion, thereby furnishing invaluable insights for designing and optimizing low-voltage circuit breakers.

关键词： Magnetohydrodynamics Electromagnetic forces Circuit breakers Voltage optimization Integrated circuit modeling Iron Atmospheric modeling Low voltage Conductivity Arc-extinguishing structure low-voltage dc circuit breaker magnetohydrodynamic (MHD) multiobjective optimization

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multiobjective optimization of laminated composite plates using metaheuristic algorithms

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MECHANICS BASED DESIGN OF STRUCTURES AND MACHINES 2025年第5期53卷 3416-3433页

作者： Sager, Guilherme Hofstadler, Franz Grotti, Ewerton Santana, Pedro Buhrer Casas, Walter Jesus Paucar Gomes, Herbert Martins Univ Fed Rio Grande do Sul Dept Mech Engn Porto Alegre RS Brazil

This study introduces a multiobjective optimization algorithm for composite laminates, targeting natural frequencies, internal stresses, and buckling resistance with ply orientation as a primary design variable. Validated against experimental data, the algorithm allows for tailored designs focused on dynamic performance, strength, or buckling needs. Four cases are analyzed, including a graphite-epoxy composite optimized for multiple objectives, showing the significant impact of fiber orientation on achieving specific structural requirements. By generating effective Pareto fronts across varying design constraints, the method provides a scalable approach for complex laminate optimization. This research fills a literature gap, balancing computational efficiency with accuracy compared to benchmark problems.

关键词： Laminated composites stacking sequence optimization multiobjective optimization frequency and buckling constraints differential evolution optimization

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multiobjective optimization of Three-Pass Perforated Muffler Design for Improved Acoustic Performance and Reduced Fluid Pressure Drop Using Genetic Algorithms

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INTERNATIONAL JOURNAL OF AUTOMOTIVE AND MECHANICAL ENGINEERING 2025年第1期22卷 12074-12090页

作者： Suprayitno Pratama, Muhammad Yandi Univ Negeri Malang Dept Mech & Ind Engn Malang 65145 Indonesia

Noise pollution is a serious problem as the vehicle population increases every year. The vehicle exhaust system is a major contributor to noise pollution, while mufflers play a vital role in reducing it. Among various designs, a three-pass perforated is a muffler design that is often used to reduce noise in the vehicle exhaust system. However, a good muffler design should also consider minimizing the pressure drop, where these two requirements conflict. To solve this problem, a multiobjective optimization approach was applied using a non-dominated sorting genetic algorithm (NSGA-II) to find the optimal muffler design solution. Analysis of Variance (ANOVA) was also presented in this study as a statistical tool to determine the muffler design parameters that have a significant effect. To predict the acoustic transmission loss (TL) and fluid pressure drop (PD) inside the muffler, the three-pass perforated was simulated and experimentally verified. The results present two optimal muffler designs that were selected and discussed. The best designs are TL and experiment no.26. The best design TL, produced a muffler with a noise reduction capability (TL) better than the initial design by 9 dBA or 48%, with a PD improvement of 87.3 Pa or 2%. Experimental design no. 26 offers mufflers with noise reduction capability (TL) better than the initial design by 3.2 dBA or 18%, with an improvement in PD of 19.9 Pa or 0.5%. These results offer an alternative muffler design solution that has better noise reduction capability with a small increase in PD. ANOVA results with a significance level of 0.05 show that the design hole diameter parameter has a significant influence on TL performance, as evidenced by a p-value smaller than 0.05. Meanwhile, the ANOVA results for PD performance concluded that none of the design parameters or their interactions had a significant influence on PD performance. Only the design parameter center width and its squared interaction are assumed to have a sign

关键词： multiobjective optimization Three-Pass Perforated Muffler Transmission Loss Pressure Drop NSGA-II

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HK-MOEA/D: A historical knowledge-guided resource allocation for decomposition multiobjective optimization

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ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 2025年 139卷

作者： Li, Wei Zeng, Xiaolong Huang, Ying Cheung, Yiu-ming Jiangxi Univ Sci & Technol Sch Informat Engn Ganzhou 341000 Peoples R China Gannan Normal Univ Sch Math & Comp Sci Ganzhou 341000 Peoples R China Hong Kong Baptist Univ Dept Comp Sci Hong Kong Peoples R China

Decomposition-based multiobjective evolutionary algorithms is one of the prevailing algorithmic frameworks for multiobjective optimization. This framework distributes the same amount of evolutionary computing resources to each subproblems, but it ignores the variable contributions of different subproblems to population during the evolution. Resource allocation strategies (RAs) have been proposed to dynamically allocate appropriate evolutionary computational resources to different subproblems, with the aim of addressing this limitation. However, the majority of RA strategies result in inefficiencies and mistakes when performing subproblem assessment, thus generating unsuitable algorithmic results. To address this problem, this paper proposes a decomposition-based multiobjective evolutionary algorithm (HK-MOEA/D). The HK-MOEA/D algorithm uses a historical knowledge-guided RA strategy to evaluate the subproblem's evolvability, allocate evolutionary computational resources based on the evaluation value, and adaptively select genetic operators based on the evaluation value to either help the subproblem converge or move away from a local optimum. Additionally, the density-first individual selection mechanism of the external archive is utilized to improve the diversity of the algorithm. An external archive update mechanism based on theta-dominance is also used to store solutions that are truly worth keeping to guide the evaluation of subproblem evolvability. The efficacy of the proposed algorithm is evaluated by comparing it with seven state-of-the-art algorithms on three types of benchmark functions and three types of real-world application problems. The experimental results show that HK-MOEA/D accurately evaluates the evolvability of the subproblems and displays reliable performance in a variety of complex Pareto front optimization problems.

关键词： Decomposition Subproblem evolvability Evolutionary computational resource Allocation multiobjective optimization

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