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Journal articles on the topic 'Multiobjective synthesis'

Author: Grafiati

Published: 30 May 2022

Last updated: 31 July 2025

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1

Liu, Yan, Yong-Chang Jiao, Ya-Ming Zhang, and Yan-Yan Tan. "Synthesis of Phase-Only Reconfigurable Linear Arrays Using Multiobjective Invasive Weed Optimization Based on Decomposition." International Journal of Antennas and Propagation 2014 (2014): 1–11. http://dx.doi.org/10.1155/2014/630529.

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Synthesis of phase-only reconfigurable array aims at finding a common amplitude distribution and different phase distributions for the array to form different patterns. In this paper, the synthesis problem is formulated as a multiobjective optimization problem and solved by a new proposed algorithm MOEA/D-IWO. First, novel strategies are introduced in invasive weed optimization (IWO) to make original IWO fit for solving multiobjective optimization problems; then, the modified IWO is integrated into the framework of the recently well proved competitive multiobjective optimization algorithm MOEA

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2

da Cruz, André R., Rodrigo T. N. Cardoso, and Ricardo H. C. Takahashi. "Multiobjective synthesis of robust vaccination policies." Applied Soft Computing 50 (January 2017): 34–47. http://dx.doi.org/10.1016/j.asoc.2016.11.010.

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3

Pappula, Lakshman, and Debalina Ghosh. "Synthesis of Thinned Planar Antenna Array Using Multiobjective Normal Mutated Binary Cat Swarm Optimization." Applied Computational Intelligence and Soft Computing 2016 (2016): 1–9. http://dx.doi.org/10.1155/2016/4102156.

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The process of thinned antenna array synthesis involves the optimization of a number of mutually conflicting parameters, such as peak sidelobe level, first null beam width, and number of active elements. This necessitates the development of a multiobjective optimization approach which will provide the best compromised solution based on the application at hand. In this paper, a novel multiobjective normal mutated binary cat swarm optimization (MO-NMBCSO) is developed and proposed for the synthesis of thinned planar antenna arrays. Through this method, a high degree of flexibility is introduced

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Kelaiaia, Ridha, Olivier Company, and Abdelouahab Zaatri. "Multiobjective optimization of parallel kinematic mechanisms by the genetic algorithms." Robotica 30, no. 5 (2011): 783–97. http://dx.doi.org/10.1017/s0263574711001032.

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SUMMARYIt is well known that Parallel Kinematic Mechanisms (PKMs) have an intrinsic dynamic potential (very high speed and acceleration) with high precision and high stiffness. Nevertheless, the choice of optimal dimensions that provide the best performances remains a difficult task, since performances strongly depend on dimensions. On the other hand, there are many criteria of performance that must be taken into account for dimensional synthesis, and which are sometimes antagonist. This paper presents an approach of multiobjective optimization for PKMs that takes into account several criteria

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5

Kuznetsov, B. I., T. B. Nikitina, and I. V. Bovdui. "MULTIOBJECTIVE SYNTHESIS OF TWO DEGREE OF FREEDOM NONLINEAR ROBUST CONTROL BY DISCRETE CONTINUOUS PLANT." Tekhnichna Elektrodynamika 2020, no. 5 (2020): 10–14. http://dx.doi.org/10.15407/techned2020.05.010.

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6

Degtyarev, G. L., R. N. Faizutdinov, and I. O. Spiridonov. "Multiobjective Robust Controller Synthesis for Nonlinear Mechanical System." Mekhatronika, Avtomatizatsiya, Upravlenie 19, no. 11 (2018): 691–98. http://dx.doi.org/10.17587/mau.19.691-698.

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In the paper multiobjective robust controller synthesis problem for nonlinear mechanical system described by Lagrange’s equations of the second kind is considered. Such tasks have numerous practical applications, for example in controller design of robotic systems and gyro-stabilized platforms. In practice, we often have to use uncertain mathematical plant models in controller design. Therefore, ensuring robustness in presence of parameters perturbations and unknown external disturbances is an important requirement for designed systems. Much of modern robust control theory is linear. When the

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7

Di Barba, Paolo, Maria Evelina Mognaschi, Paolo Venini, and Slavomir Wiak. "Biogeography-inspired multiobjective optimization for helping MEMS synthesis." Archives of Electrical Engineering 66, no. 3 (2017): 607–23. http://dx.doi.org/10.1515/aee-2017-0046.

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AbstractThe aim of the paper is to assess the applicability of a multi-objective biogeography-based optimisation algorithm in MEMS synthesis. In order to test the performances of the proposed method in this research field, the optimal shape design of an electrostatic micromotor, and two different electro-thermo-elastic microactuators are considered as the case studies.

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8

Li, Wentao, Yongqiang Hei, Jing Yang, and Xiaowei Shi. "3D Pattern Synthesis of Time-Modulated Conformal Arrays with a Multiobjective Optimization Approach." International Journal of Antennas and Propagation 2014 (2014): 1–12. http://dx.doi.org/10.1155/2014/687124.

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This paper addresses the synthesis of the three-dimensional (3D) radiation patterns of the time-modulated conformal arrays. Due to the nature of periodic time modulation, harmonic radiation patterns are generated at the multiples of the modulation frequency in time-modulated arrays. Thus, the optimization goal of the time-modulated conformal array includes the optimization of the sidelobe level at the operating frequency and the sideband levels (SBLs) at the harmonic frequency, and the design can be regarded as a multiobjective problem. The multiobjective particle swarm optimization (MOPSO) is

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9

Reyes Fernandez de Bulnes, Darian, Yazmin Maldonado, and Leonardo Trujillo. "Development of Multiobjective High-Level Synthesis for FPGAs." Scientific Programming 2020 (June 29, 2020): 1–25. http://dx.doi.org/10.1155/2020/7095048.

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Traditionally, the High-Level Synthesis (HLS) for Field Programmable Gate Array (FPGA) devices is a methodology that transforms a behavioral description, as the timing-independent specification, to an abstraction level that is synthesizable, like the Register Transfer Level. This process can be performed under a framework that is known as Design Space Exploration (DSE), which helps to determine the best design by addressing scheduling, allocation, and binding problems, all three of which are NP-hard problems. In this manner, and due to the increased complexity of modern digital circuit designs

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10

Kravanja, Z., M. Ropotar, and Z. N. Pintarič. "Two-step multiobjective synthesis of sustainable chemical processes." Theoretical Foundations of Chemical Engineering 46, no. 6 (2012): 681–90. http://dx.doi.org/10.1134/s0040579512060140.

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11

Yagoubi, M. "On multiobjective synthesis for parameter-dependent descriptor systems." IET Control Theory & Applications 4, no. 5 (2010): 817–26. http://dx.doi.org/10.1049/iet-cta.2009.0149.

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12

del Rio-Chanona, Ehecatl Antonio, Dongda Zhang, and Nilay Shah. "Sustainable biopolymer synthesis via superstructure and multiobjective optimization." AIChE Journal 64, no. 1 (2017): 91–103. http://dx.doi.org/10.1002/aic.15877.

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13

Duminică, Despina, Iulian Dutu, Mihai Avram, and Viorel Gheorghe. "Fuzzy Multiobjective Optimization Used in Tolerance Synthesis of Mechanisms." Applied Mechanics and Materials 332 (July 2013): 235–40. http://dx.doi.org/10.4028/www.scientific.net/amm.332.235.

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Fuzzy objective multioptimization describes performance criteria and constraints in terms of fuzzy membership functions. The membership function of the decision is obtained as conjunction of performance criteria and constraints. A method of allocating tolerance intervals using fuzzy multiobjective optimization is presented for the case of a 3R manipulator. The proposed method is validated through Monte Carlo simulation.

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14

Kuznetsov, Borys, Ihor Bovdui, Tatyana Nikitina, Valeriy Kolomiets, and Borys Kobylianskyi. "Electromechanical servo system with anisotropic regulator." Computational Problems of Electrical Engineering 8, no. 2 (2018): 49–58. http://dx.doi.org/10.23939/jcpee2018.02.049.

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A method of multiobjective synthesis for nonlinear multi-mass electromechanical servo systems with uncertain plant parameters based on feed-forward robust stochastic anisotropic control to improve the accuracy of such systems is developed. The method is based on the choice of the robust control target vector by solving the corresponding problem of multiobjective nonlinear programming in which the components of the target function vectors are direct quality indicators that are specified to the system in various modes of its operation. The calculation of the target function vector componentrs an

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15

Ben Aicha, Faten, Faouzi Bouani, and Mekki Ksouri. "A multivariable multiobjective predictive controller." International Journal of Applied Mathematics and Computer Science 23, no. 1 (2013): 35–45. http://dx.doi.org/10.2478/amcs-2013-0004.

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Predictive control of MIMO processes is a challenging problem which requires the specification of a large number of tuning parameters (the prediction horizon, the control horizon and the cost weighting factor). In this context, the present paper compares two strategies to design a supervisor of the Multivariable Generalized Predictive Controller (MGPC), based on multiobjective optimization. Thus, the purpose of this work is the automatic adjustment of the MGPC synthesis by simultaneously minimizing a set of closed loop performances (the overshoot and the settling time for each output of the MI

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16

Kagami, Ricardo Massao, Roberto Zanetti Freire, and Gilberto Reynoso-Meza. "Multiobjective Robust PI Synthesis in Plants with Uncertain Poles." IFAC-PapersOnLine 58, no. 7 (2024): 174–79. http://dx.doi.org/10.1016/j.ifacol.2024.08.030.

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17

Li, Xun, Kwai Man Luk, and Baoyan Duan. "Multiobjective Optimal Antenna Synthesis for Microwave Wireless Power Transmission." IEEE Transactions on Antennas and Propagation 67, no. 4 (2019): 2739–44. http://dx.doi.org/10.1109/tap.2019.2893312.

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18

Li, Zhao, and James Lam. "Multiobjective controller synthesis via eigenstructure assignment with state feedback." International Journal of Systems Science 47, no. 13 (2015): 3219–31. http://dx.doi.org/10.1080/00207721.2015.1112444.

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19

Chakraborty, Aninda, and Andreas A. Linninger. "Plant-Wide Waste Management. 1. Synthesis and Multiobjective Design." Industrial & Engineering Chemistry Research 41, no. 18 (2002): 4591–604. http://dx.doi.org/10.1021/ie010741o.

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20

Papadopoulos, Athanasios I., and Patrick Linke. "Multiobjective molecular design for integrated process-solvent systems synthesis." AIChE Journal 52, no. 3 (2006): 1057–70. http://dx.doi.org/10.1002/aic.10715.

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21

Liang, Weilong, Zhao Wu, and Li Zhang. "Multiobjective Optimization Design of Time-Modulated Concentric Circular Ring Arrays." International Journal of Antennas and Propagation 2018 (2018): 1–8. http://dx.doi.org/10.1155/2018/6056139.

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A multiobjective approach based on the third evolution step of generalized differential evolution (GDE3) algorithm is proposed for optimizing the time-modulated array (TMA) in this paper. Different from the single-objective optimization, which optimizes a weighted sum of the peak sidelobe level (PSLL) and the peak sideband level (PSBL) of the array, the multiobjective algorithm treats the PSLL and the PSBL as two distinct objectives that are to be optimized simultaneously. Furthermore, not only one outstanding optimization result can be acquired but also a set of solutions known as Pareto fron

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22

Garza, Leopoldo A., Marco A. Panduro, David H. Covarrubias, and Alberto Reyna. "Multiobjective Synthesis of Steerable UWB Circular Antenna Array considering Energy Patterns." International Journal of Antennas and Propagation 2015 (2015): 1–9. http://dx.doi.org/10.1155/2015/789094.

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True-time delay antenna arrays have gained a prominent attention in ultrawideband (UWB) applications such as directional communications and radar. This paper presents the design of steerable UWB circular array by using a multiobjective time-domain synthesis of energy pattern for circular antenna arrays. By this way we avoid individual beamforming for each frequency in UWB spectrum if the problem was addressed from the frequency domain. In order to obtain an energy pattern with low side lobe level and a desired main beam, the synthesis presented is performed by optimizing the true-time delays a

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23

Mora Paz, Jaime David, and Oscar Darío Tascón Muñoz. "Multiobjective Optimization of a Submarine Hull Design." Ciencia y tecnología de buques 7, no. 14 (2014): 27. http://dx.doi.org/10.25043/19098642.92.

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A synthesis model for the concept design of a submarine is developed consisting of a parametric definition of the hull geometry, a maneuverability model based on slender-body theory, and a resistance formulation. This coupled model is suitable to be treated by a metaheuristic multiobjective optimization technique (a genetic algorithm) to find a set of design options that satisfy the need to minimize simultaneously the turning diameter and the resistance generated. According to typical data found in submarines like the one analyzed herein, the boundaries and some constraints are set for the des

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24

Yang, Bo. "Multiobjective Synthesis of Linear Arrays by Using an Improved Genetic Algorithm." International Journal of Antennas and Propagation 2019 (July 22, 2019): 1–13. http://dx.doi.org/10.1155/2019/1064103.

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In this paper, an improved genetic algorithm with dynamic weight vector (IGA-DWV) is proposed for the pattern synthesis of a linear array. To maintain the diversity of the selected solution in each generation, the objective function space is divided by the dynamic weight vector, which is uniformly distributed on the Pareto front (PF). The individuals closer to the dynamic weight vector can be chosen to the new population. Binary- and real-coded genetic algorithms (GAs) with a mapping method are implemented for different optimization problems. To reduce the computation complexity, the repeat ca

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25

Karimzadeh Baee, Roghieh, Keyvan Forooraghi, and Somayyeh Chamaani. "Conformal Array Pattern Synthesis Using a Hybrid WARP/2LB-MOPSO Algorithm." International Journal of Antennas and Propagation 2012 (2012): 1–7. http://dx.doi.org/10.1155/2012/202906.

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This paper addresses conformal array synthesis as a constrained multiobjective optimization problem. Simultaneous reduction of side lobe level (SLL) and cross-polarization (XPL) level is aimed with a constraint on main beam direction. A hybrid of weighted alternating reverse projection (WARP) and two local best multiobjective particle swarm optimization (2LB-MOPSO) is proposed to optimize the pattern. First, the WARP method finds a moderate and feasible solution. Second, 2LB-MOPSO begins with an initial population including the solution of WARP and penalty functions for constraint handling. In

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26

HASHIBA, Takayuki, Satoshi GAMOU, Shu YOSHIDA, Koichi ITO, and Ryohei YOKOYAMA. "305 Multiobjective Optimization for Structural Synthesis of Energy Supply Systems." Proceedings of Conference of Kansai Branch 2005.80 (2005): _3–9_—_3–10_. http://dx.doi.org/10.1299/jsmekansai.2005.80._3-9_.

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27

Han, C., L. Wang, Z. Zhang, J. Xie, and Z. Xing. "Linear Array Pattern Synthesis Using An Improved Multiobjective Genetic Algorithm." Radioengineering 26, no. 4 (2017): 1048–59. http://dx.doi.org/10.13164/re.2017.1048.

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28

YOSHIDA, Shu, Satoshi GAMOU, Koichi ITO, Ryohei YOKOYAMA, and Takayuki HASHIBA. "Structural Synthesis of Energy Supply Systems by Multiobjective Optimization Approach." Transactions of the Japan Society of Mechanical Engineers Series B 70, no. 699 (2004): 3008–15. http://dx.doi.org/10.1299/kikaib.70.3008.

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29

Pelosi, Giuseppe, Stefano Selleri, and Ruggero Taddei. "A Novel Multiobjective Taguchi's Optimization Technique for Multibeam Array Synthesis." Microwave and Optical Technology Letters 55, no. 8 (2013): 1836–40. http://dx.doi.org/10.1002/mop.27705.

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30

Ebihara, Yoshio, and Tomomichi Hagiwara. "New dilated LMI characterizations for continuous-time multiobjective controller synthesis." Automatica 40, no. 11 (2004): 2003–9. http://dx.doi.org/10.1016/j.automatica.2004.06.009.

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31

Kuznetsov, B., T. Nikitina, and I. Bovdui. "Magnetic Field Active Shielding of Overhead Power Lines with Triangular Phase Conductors Arrangements." Problemele Energeticii Regionale 1(45) (January 15, 2020): 14–29. https://doi.org/10.5281/zenodo.3713400.

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The purpose of the work is synthesis of two degree of freedom robust two circuits system of active shielding of magnetic field, generated by overhead power lines with triangular phase conductor’s arrangements for reducing the initial magnetic flux density to the sanitary standards level and reducing the system sensitivity to the plant parameters variations. Two circuits system of active shielding includes two shielding coils. System of active shielding synthesis reduced to the multiobjective stochastic game solution, in which the vector payoff is calculated on the basis of the Maxwell eq

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32

Dhingra, A. K., and S. S. Rao. "An Integrated Kinematic-Kinetostatic Approach to Optimal Design of Planar Mechanisms Using Fuzzy Theories." Journal of Mechanical Design 113, no. 3 (1991): 306–11. http://dx.doi.org/10.1115/1.2912783.

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A new integrated approach to the design of high speed planar mechanisms is presented. The resulting nonlinear programming formulation combines both the kinematic and kinetostatic synthesis aspects of mechanism design. The multiobjective optimization techniques presented in this work facilitate the design of a linkage to meet several kinematic and dynamic design criteria. The method can be used for motion, path, and function generation problems. The nonlinear programming formulation also permits an imposition of constraints to eliminate solutions which possess undesirable kinematic and motion c

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33

Mitrev, Rosen, and Todor Todorov. "Multicriteria optimal selection of a hydraulic cylinder for drive mechanisms." FME Transactions 49, no. 2 (2021): 501–10. http://dx.doi.org/10.5937/fme2102501m.

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The paper reports the optimization synthesis of a hydraulically actuated drive mechanism. A mathematical model of the mechanism using vector closure equations is developed. Based on the functional purpose of the mechanism, a set of geometric and force/moment requirements are defined which must be met by a proper selection of a standardized hydraulic cylinder and its points of attachment. A multiobjective design optimization task is defined with three objective functions whose minimum is searched - the mass of the hydraulic cylinder, the squared total deviation of the developed by the hydraulic

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34

Iannelli, Andrea, and Roy S. Smith. "A Multiobjective LQR Synthesis Approach to Dual Control for Uncertain Plants." IEEE Control Systems Letters 4, no. 4 (2020): 952–57. http://dx.doi.org/10.1109/lcsys.2020.2997085.

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35

Ho, S. L., and Shiyou Yang. "Multiobjective Synthesis of Antenna Arrays Using a Vector Tabu Search Algorithm." IEEE Antennas and Wireless Propagation Letters 8 (2009): 947–50. http://dx.doi.org/10.1109/lawp.2009.2029135.

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36

Hoffmann, A. F., and F. A. Weiβ. "Controller design for wind turbine load reduction via multiobjective parameter synthesis." Journal of Physics: Conference Series 753 (September 2016): 052020. http://dx.doi.org/10.1088/1742-6596/753/5/052020.

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37

Bachur, Wagner Eustáquio Gomes, Eduardo Nunes Gonçalves, Jaime Arturo Ramírez, and Lucas S. Batista. "A multiobjective robust controller synthesis approach aided by multicriteria decision analysis." Applied Soft Computing 60 (November 2017): 374–86. http://dx.doi.org/10.1016/j.asoc.2017.06.027.

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38

Ferrari, S. "Multiobjective Algebraic Synthesis of Neural Control Systems by Implicit Model Following." IEEE Transactions on Neural Networks 20, no. 3 (2009): 406–19. http://dx.doi.org/10.1109/tnn.2008.2008332.

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39

Mulder, Eric F., Pradeep Y. Tiwari, and Mayuresh V. Kothare. "Simultaneous linear and anti-windup controller synthesis using multiobjective convex optimization." Automatica 45, no. 3 (2009): 805–11. http://dx.doi.org/10.1016/j.automatica.2008.10.019.

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40

Li, Xin, Wen-Tao Li, Xiao-Wei Shi, and Jing Yang. "Synthesis of antenna arrays with an efficient multiobjective differential evolution algorithm." International Journal of RF and Microwave Computer-Aided Engineering 24, no. 2 (2013): 161–69. http://dx.doi.org/10.1002/mmce.20744.

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41

Yavari, Reza, Arash Sadeghzadeh, and Saeed Shamaghdari. "Improved multiobjective switching gain‐scheduled controller synthesis exploiting inexact scheduling parameters." International Journal of Robust and Nonlinear Control 30, no. 17 (2020): 7706–30. http://dx.doi.org/10.1002/rnc.5203.

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42

Campbell, Matthew I., Jonathan Cagan, and Kenneth Kotovsky. "Agent-Based Synthesis of Electromechanical Design Configurations." Journal of Mechanical Design 122, no. 1 (2000): 61–69. http://dx.doi.org/10.1115/1.533546.

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A new automated approach to engineering design known as A-design is presented that creates design configurations through the interaction of software agents. By combining unique problem solving strategies, these agents are able to generate solutions to open-ended design problems. The A-design methodology makes several theoretical claims through its combination of multiagent systems, multiobjective design selection, and stochastic optimization, and is currently implemented to solve general electromechanical design problems. While this paper presents an overview of the theoretical basis for A-des

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43

Chen, Zhi-Kun, Feng-Gang Yan, Xiao-Lin Qiao, and Yi-Nan Zhao. "Sparse Antenna Array Design for MIMO Radar Using Multiobjective Differential Evolution." International Journal of Antennas and Propagation 2016 (2016): 1–12. http://dx.doi.org/10.1155/2016/1747843.

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A two-stage design approach is proposed to address the sparse antenna array design for multiple-input multiple-output radar. In the first stage, the cyclic algorithm (CA) is used to establish a covariance matrix that satisfies the beam pattern approximation for a full array. In the second stage, a sparse antenna array with a beam pattern is designed to approximate the desired beam pattern. This paper focuses on the second stage. The optimization problem for the sparse antenna array design aimed at beam pattern synthesis is formulated, where the peak side lobe (PSL) is weakly constrained by the

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44

Williamson, Emily M., Bryce A. Tappan, Lucía Mora-Tamez, Gözde Barim, and Richard L. Brutchey. "Statistical Multiobjective Optimization of Thiospinel CoNi2S4 Nanocrystal Synthesis via Design of Experiments." ACS Nano 15, no. 6 (2021): 9422–33. http://dx.doi.org/10.1021/acsnano.1c00502.

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45

Chen, Chiu-hung, Tung-kuan Liu, I.-ming Huang, and Jyh-horng Chou. "Multiobjective Synthesis of Six-Bar Mechanisms Under Manufacturing and Collision-Free Constraints." IEEE Computational Intelligence Magazine 7, no. 1 (2012): 36–48. http://dx.doi.org/10.1109/mci.2011.2176996.

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Jena, Rabindra Kumar, and Gopal K. Sharma. "A multiobjective evolutionary algorithm-based optimisation model for network on chip synthesis." International Journal of Innovative Computing and Applications 1, no. 2 (2007): 121. http://dx.doi.org/10.1504/ijica.2007.016793.

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47

Cabrera, J. A., F. Nadal, J. P. Muñoz, and A. Simon. "Multiobjective constrained optimal synthesis of planar mechanisms using a new evolutionary algorithm." Mechanism and Machine Theory 42, no. 7 (2007): 791–806. http://dx.doi.org/10.1016/j.mechmachtheory.2006.07.004.

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48

Firth, Nicholas C., Butrus Atrash, Nathan Brown, and Julian Blagg. "MOARF, an Integrated Workflow for Multiobjective Optimization: Implementation, Synthesis, and Biological Evaluation." Journal of Chemical Information and Modeling 55, no. 6 (2015): 1169–80. http://dx.doi.org/10.1021/acs.jcim.5b00073.

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49

Dehghanian, Effat, and Saman Zare Gheshlaghi. "A multiobjective approach in constructing a predictive model for Fischer-Tropsch synthesis." Journal of Chemometrics 32, no. 3 (2017): e2969. http://dx.doi.org/10.1002/cem.2969.

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Mohanty, Swati. "Multiobjective optimization of synthesis gas production using non-dominated sorting genetic algorithm." Computers & Chemical Engineering 30, no. 6-7 (2006): 1019–25. http://dx.doi.org/10.1016/j.compchemeng.2006.01.002.

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