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Journal articles on the topic 'Multiobjective synthesis'

Author: Grafiati

Published: 30 May 2022

Last updated: 31 May 2022

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1

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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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 (August 25, 2020): 10–14. http://dx.doi.org/10.15407/techned2020.05.010.

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3

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/D to form a new competitive MOEA/D-IWO algorithm. At last, two sets of experiments are carried out to illustrate the effectiveness of MOEA/D-IWO. In addition, MOEA/D-IWO is compared with MOEA/D-DE, a new version of MOEA/D. The comparing results show the superiority of MOEA/D-IWO and indicate its potential for solving the antenna array synthesis problems.

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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 to the realm of thinned array design. A Pareto-optimal front containing all the probable designs is obtained in this process. Targeted solutions may be chosen from the Pareto front to satisfy the different requirements demonstrating the superiority of the proposed approach over multiobjective binary particle swarm optimization method (MO-BPSO). A comparative study is carried out to quantify the performance of the two algorithms using two performance metrics.

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Degtyarev, G. L., R. N. Faizutdinov, and I. O. Spiridonov. "Multiobjective Robust Controller Synthesis for Nonlinear Mechanical System." Mekhatronika, Avtomatizatsiya, Upravlenie 19, no. 11 (November 8, 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 actual system exhibits nonlinear behavior, nonlinearities are usually included in the uncertainty set of the plant. A disadvantage of this approach is that resulting controllers may be too conservative especially when nonlinearities are significant. The nonlinear H∞ optimal control theory developed on the basis of differential game theory is a natural extension of the linear robust control theory. Nonlinear theory methods ensure robust stability of designed control systems. However, to determine nonlinear H∞-control law, the partial differential equation have to be solved which is a rather complicated task. In addition, it is difficult to ensure robust performance of controlled processes when using this method. In this paper, methods of linear parameter-varying (LPV) systems are used to synthesize robust control law. It is shown, that Lagrange system may be adequately represented in the form of quasi-LPV model. From the computational point of view, the synthesis procedure is reduced to convex optimization techniques under constraints expressed in the form of linear matrix inequalities (LMIs). Measured parameters are incorporated in the control law, thus ensuring continuous adjustment of the controller parameters to the current plant dynamics and better performance of control processes in comparison with H∞-regulators. Furthermore, the use of the LMIs allows to take into account the transient performance requirements in the controller synthesis. Since the quasi-LPV system depends continuously on the parameter vector, the LMI system is infinite-dimensional. This infinitedimensional system is reduced to a finite set of LMIs by introducing a polytopic LPV representation. The example of multiobjective robust control synthesis for electro-optical device’s line of sight pointing and stabilization system suspended in two-axes inertially stabilized platform is given.

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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 (September 1, 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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Kelaiaia, Ridha, Olivier Company, and Abdelouahab Zaatri. "Multiobjective optimization of parallel kinematic mechanisms by the genetic algorithms." Robotica 30, no. 5 (September 30, 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 of performance simultaneously that have a direct impact on the dimensional synthesis of PKMs. We first present some criteria of performance such as the workspace, transmission speeds, stiffness, dexterity, precision, as well as dynamic dexterity. Secondly, we present the problem of dimensional synthesis, which will be defined as a multiobjective optimization problem. The method of genetic algorithms is used to solve this type of multiobjective optimization problem by means of NSGA-II and SPEA-II algorithms. Finally, based on a linear Delta architecture, we present an illustrative application of this methodology to a 3-axis machine tool in the context of manufacturing of automotive parts.

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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 and concerns regarding the capacity of the FPGAs, designers are proposing novel HLS techniques capable of performing automatic optimization. HLS has several conflicting metrics or objective functions, such as delay, area, power, wire length, digital noise, reliability, and security. For this reason, it is suitable to apply Multiobjective Optimization Algorithms (MOAs), which can handle the different trade-offs among the objective functions. During the last two decades, several MOAs have been applied to solve this problem. This paper introduces a comprehensive analysis of different MOAs that are suitable to perform HLS for FPGA devices. We highlight significant aspects of MOAs, namely, optimization methods, intermediate structures where the optimizations are performed, HLS techniques that are addressed, and benchmarks and performance assessments employed for experimentation. In addition, we show the analysis of how multiple objectives are optimized currently in the algorithms and which are the objective functions that are optimized. Finally, we provide insights and suggestions to contribute to the solution of major research challenges in this area.

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

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10

del Rio-Chanona, Ehecatl Antonio, Dongda Zhang, and Nilay Shah. "Sustainable biopolymer synthesis via superstructure and multiobjective optimization." AIChE Journal 64, no. 1 (July 31, 2017): 91–103. http://dx.doi.org/10.1002/aic.15877.

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11

Yagoubi, M. "On multiobjective synthesis for parameter-dependent descriptor systems." IET Control Theory & Applications 4, no. 5 (May 1, 2010): 817–26. http://dx.doi.org/10.1049/iet-cta.2009.0149.

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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 applied to optimize the switch-on instants and pulse durations of the time-modulated conformal array. To significantly reduce the optimization variables, the modified Bernstein polynomial is employed in the synthesis process. Furthermore, dual polarized patch antenna is designed as radiator to achieve low cross-polarization level during the beam scanning. A 12 × 13 (156)-element conical conformal microstrip array is simulated to demonstrate the proposed synthesis mechanism, and good results reveal the promising ability of the proposed algorithm in solving the synthesis of the time-modulated conformal arrays problem.

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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

Ben Aicha, Faten, Faouzi Bouani, and Mekki Ksouri. "A multivariable multiobjective predictive controller." International Journal of Applied Mathematics and Computer Science 23, no. 1 (March 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 MIMO system). First, we adopt the Weighted Sum Method (WSM), which is an aggregative method combined with a Genetic Algorithm (GA) used to minimize a single criterion generated by the WSM. Second, we use the Non- Dominated Sorting Genetic Algorithm II (NSGA-II) as a Pareto method and we compare the results of both the methods. The performance of the two strategies in the adjustment of multivariable predictive control is illustrated by a simulation example. The simulation results confirm that a multiobjective, Pareto-based GA search yields a better performance than a single objective GA.

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

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16

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 (April 2019): 2739–44. http://dx.doi.org/10.1109/tap.2019.2893312.

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17

Li, Zhao, and James Lam. "Multiobjective controller synthesis via eigenstructure assignment with state feedback." International Journal of Systems Science 47, no. 13 (November 18, 2015): 3219–31. http://dx.doi.org/10.1080/00207721.2015.1112444.

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18

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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19

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 and amplitude coefficients for the antenna elements in a circular geometry. The method of Differential Evolution for Multiobjective Optimization (DEMO) is used as the optimization algorithm in this work. This design of steerable UWB circular arrays considers the optimization of the true-time exciting delays and the amplitude coefficients across the antenna elements to operate with optimal performance in the whole azimuth plane (360°). A comparative analysis of the performance of the optimized design with the case of conventional progressive delay excitations is achieved. The provided results show a good performance for energy patterns and for their respective power patterns in the UWB spectrum.

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20

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 calculation of the fitness function in each generation is replaced by a precomputed discrete cosine transform matrix. By transforming the array pattern synthesis into a multiobjective optimization problem, the conflict among the side lobe level (SLL), directivity, and nulls can be efficiently addressed. The proposed method is compared with real number particle swarm optimization (RNPSO) and quantized particle swarm optimization (QPSO) as applied in the pattern synthesis of a linear thinned array and a digital phased array. The numerical examples show that IGA-DWV can achieve a high performance with a lower SLL and more accurate nulls.

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Mora Paz, Jaime David, and Oscar Darío Tascón Muñoz. "Multiobjective Optimization of a Submarine Hull Design." Ciencia y tecnología de buques 7, no. 14 (January 26, 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 design variables. Finally, some solutions for this design case are obtained considering the criteria adopted in this study.

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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 (December 14, 2017): 1048–59. http://dx.doi.org/10.13164/re.2017.1048.

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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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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 (May 28, 2013): 1836–40. http://dx.doi.org/10.1002/mop.27705.

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

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27

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 front is obtained by using the GDE3 algorithm, which will guide the design of time-modulated array more effectively. Users can choose one appropriate outcome which has a suitable tradeoff between the PSLL and the PSBL. This approach is illustrated through a time-modulated concentric circular ring array (CCRA). The optimal parameters and the corresponding radiation patterns are presented at last. Experimental results reveal that the multiobjective optimization can be an effective approach for the TMA synthesis problems.

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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. Involving WARP result in the initial population of 2LB-MOPSO leads to higher convergence rate, avoiding local extermum traps and less sensitivity to penalty functions. Compared to WARP method which stagnates rapidly, the proposed hybrid method gives better SLL and XPL after adequate iterations. In addition, as 2LB-MOPSO offers a set of optimum solutions (Pareto front) instead of a single solution, this method provides more degrees of freedom in selection of proper practical arrays. Finally, to examine the mutual coupling consideration in array design, the same procedure was applied ignoring the mutual coupling between elements. The results show that the SLL and XPL strongly depend on mutual coupling.

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

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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 (June 6, 2013): 161–69. http://dx.doi.org/10.1002/mmce.20744.

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

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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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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 (March 2009): 805–11. http://dx.doi.org/10.1016/j.automatica.2008.10.019.

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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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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 (September 10, 2020): 7706–30. http://dx.doi.org/10.1002/rnc.5203.

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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 (September 1, 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 characteristics. To model the vague and imprecise information in the problem formulation, the tools of fuzzy set theory have been used. A novel method of solving the resulting fuzzy multiobjective problem using mathematical programming techniques is presented. The outlined procedure is expected to be useful in situations where doubt arises about the exactness of permissible values, degree of credibility, and correctness of statements and judgements.

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Campbell, Matthew I., Jonathan Cagan, and Kenneth Kotovsky. "Agent-Based Synthesis of Electromechanical Design Configurations." Journal of Mechanical Design 122, no. 1 (January 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-design, it primarily focuses on the method for representing electromechanical design configurations and the reasoning of the agents that construct these configurations. Results from an electromechanical test problem show the generality of the functional representation. [S1050-0472(00)00701-7]

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Behroozsarand, Alireza, and Akbar Zamaniyan. "Multiobjective optimization scheme for industrial synthesis gas sweetening plant in GTL process." Journal of Natural Gas Chemistry 20, no. 1 (January 2011): 99–109. http://dx.doi.org/10.1016/s1003-9953(10)60153-3.

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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 (July 2007): 791–806. http://dx.doi.org/10.1016/j.mechmachtheory.2006.07.004.

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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 (February 2012): 36–48. http://dx.doi.org/10.1109/mci.2011.2176996.

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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 (June 9, 2015): 1169–80. http://dx.doi.org/10.1021/acs.jcim.5b00073.

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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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Dehghanian, Effat, and Saman Zare Gheshlaghi. "A multiobjective approach in constructing a predictive model for Fischer-Tropsch synthesis." Journal of Chemometrics 32, no. 3 (November 26, 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 (May 2006): 1019–25. http://dx.doi.org/10.1016/j.compchemeng.2006.01.002.

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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 (April 20, 2021): 9422–33. http://dx.doi.org/10.1021/acsnano.1c00502.

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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 cylinder moments from the predefined values of the external moments and the force in the hydraulic cylinder. The defined multiobjective optimization task is considered as a mixed variable nonlinear constrained optimization problem containing 5 continuous and 2 discrete variables and the multistage Monte Carlo method is used for its solution. Using different weighting schemes several Pareto-optimal compromise solutions are obtained.

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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 mean squared error. To solve this optimization problem, the differential evolution (DE) algorithm with multistrategy is introduced and PSL suppression is treated as an inequality constraint. However, in doing so, a new multiobjective optimization problem is created. To address this new problem, a multiobjective differential evolution algorithm based on Pareto technique is proposed. Numerical examples are provided to demonstrate the advantages of the proposed approach over state-of-the-art methods, including DE and genetic algorithm.

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Pinchera, Daniele, Stefano Perna, and Marco Donald Migliore. "Multiobjective Optimization of a Rotman Lens through the QLWS Minimization." International Journal of Antennas and Propagation 2017 (2017): 1–6. http://dx.doi.org/10.1155/2017/3845851.

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We address the multiobjective optimization of a Rotman lens by means of a recently proposed method based on the minimization of a properly defined global cost function named Quantized Lexicographic Weighted Sum (QLWS). More specifically, we have considered three different objectives concurring during the optimal synthesis of the lens. First, the difference between actual and desired delay among the excitations of the array elements fed by the lens needs to be lower than a given threshold. Second, gain losses of the beams scanned by the array fed by the lens need to be lower than a given threshold. Third, lens insertion losses should be as low as possible. Exploitation of the QLWS based approach allowed us to obtain in a few minutes a Rotman lens fulfilling these three concurring objectives and to improve the starting result obtained by a commercial software.

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Ziyang, Zhang, K. Hidajat, and Ajay K. Ray. "Multiobjective Optimization of Simulated Countercurrent Moving Bed Chromatographic Reactor (SCMCR) for MTBE Synthesis." Industrial & Engineering Chemistry Research 41, no. 13 (June 2002): 3213–32. http://dx.doi.org/10.1021/ie0106940.

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