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multi-objective Optimization for multiphase Orbital Rendezvous Missions

JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2013年第2期36卷 622-629页

作者： Zhang, Jin Parks, Geoffrey Natl Univ Def Technol Coll Aerosp Sci & Engn Changsha 410073 Hunan Peoples R China Univ Cambridge Dept Engn Cambridge CB2 1PZ England

A multi-objective optimization approach was proposed for multiphase orbital rendezvous missions and validated by application to a representative numerical problem. By comparing the Pareto fronts obtained using the proposed method, the relationships between the three objectives considered are revealed, and the influences of other mission parameters, such as the sensors' field of view, can also be analyzed effectively. For multiphase orbital rendezvous missions, the tradeoff relationships between the total velocity increment and the trajectory robustness index as well as between the total velocity increment and the time of flight are obvious and clear. However, the tradeoff relationship between the time of flight and the trajectory robustness index is weak, especially for the four- and five-phase missions examined. The proposed approach could be used to reorganize a stable rendezvous profile for an engineering rendezvous mission, when there is a failure that prevents the completion of the nominal mission.

关键词： Orbital Rendezvous multi objective genetic algorithm Orbital Maneuvers Propellant Orbital Inclination Right Ascension Earth Optimization algorithm Nonlinear Programming Charge Coupled Device

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A novel hybrid meta-heuristic algorithm for solving multi objective flexible job shop scheduling

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JOURNAL OF MANUFACTURING SYSTEMS 2013年第4期32卷 771-780页

作者： Shahsavari-Pour, Nasser Ghasemishabankareh, Behrooz Valie E Asr Univ Dept Ind Management Rafsanjan Iran Islamic Azad Univ Dept Ind Engn Kerman Iran Islamic Azad Univ Sci & Res Branch Kerman Iran

Finding feasible scheduling that optimize all objective functions for flexible job shop scheduling problem (FJSP) is considered by many researchers. In this paper, the novel hybrid genetic algorithm and simulated annealing (NHGASA) is introduced to solve FJSP. The NHGASA is a combination of genetic algorithm and simulated annealing to propose the algorithm that is more efficient than others. The three objective functions in this paper are: minimize the maximum completion time of all the operations (makespan), minimize the workload of the most loaded machine and minimize the total workload of all machines. Pareto optimal solution approach is used in NHGASA for solving FJSP. Contrary to the other methods that assign weights to all objective functions to reduce them to one objective function, in the NHGASA and during all steps, problems are solved by three objectives. Experimental results prove that the NHGASA that uses Pareto optimal solutions for solving multi-objective FJSP overcome previous methods for solving the same benchmarks in the shorter computational time and higher quality. (C) 2013 Published by Elsevier Ltd on behalf of The Society of Manufacturing Engineers.

关键词： Flexible job shop scheduling problem Pareto optimal solution genetic algorithm Simulated annealing multi objective genetic algorithm

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A high-speed hybrid Full Adder with low power consumption

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IEICE ELECTRONICS EXPRESS 2012年第24期9卷 1900-1905页

作者： Hemmati, Kamran Delfan Fallahpour, Mojtaba Behzad Golmakani, Abbas Hemmati, Kamyar Delfan Pouyandegan & Danesh Inst Higher Educ Roshd Chalus *** Iran Islamic Azad Univ Lahijan Branch Lahijan Iran Sadjad Inst Higher Educ Mashhad 466491375 Iran Islamic Azad Univ Chalus Branch Chalus Iran

In this paper a new high speed hybrid Full Adder with low power consumption is presented. Furthermore, after determining topology a proposed CAD (Computer Aided Design) with a proposed multi objective genetic algorithm will be used to optimize the high speed hybrid Full Adder. The size of generative Full Adder transistors is introduced to algorithm as the inputs and the average power consumption and max delay are introduced as the outputs. After performing the algorithm, several results will be obtained as they have no priority to each other, so designer can select whichever according to his need. Simulation results show that, proposed structure uses less average power. algorithm program is written in MATLAB and the circuit simulated by Hspice with 0.18 mu technology.

关键词： a high speed hybrid Full Adder inverter power consumption multi objective genetic algorithm non dominated answers

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Redundancy allocation problems considering systems with imperfect repairs using multi-objective genetic algorithms and discrete event simulation

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SIMULATION MODELLING PRACTICE AND THEORY 2011年第1期19卷 362-381页

作者： Lins, Isis Didier Droguett, Enrique Lopez Univ Fed Pernambuco Ctr Estudos & Ensaios Risco & Modelagem Ambiental Dept Prod Engn BR-50740530 Recife PE Brazil

This paper considers a multi-objective genetic algorithm (GA) coupled with discrete event simulation to solve redundancy allocation problems in systems subject to imperfect repairs In the multi-objective formulation system availability and cost may be maximized and minimized respectively the failure-repair processes of system components are modeled by Generalized Renewal Processes The presented methodology provides a set of compromise solutions that incorporate not only system configurations but also the number of maintenance teams The multi-objective GA is validated via examples with analytical solutions and shows its superior performance when compared to a multi-objective Ant Colony algorithm Moreover an application example is presented and a return of investment analysis is suggested to aid the decision maker in choosing a solution of the obtained set (C) 2010 Elsevier B V All rights reserved

关键词： Redundancy allocation problems multi objective genetic algorithm Imperfect repair Reliability Maintenance

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Automated Design Optimization of a Three-Dimensional Subsonic Diffuser

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JOURNAL OF PROPULSION AND POWER 2011年第4期27卷 838-846页

作者： Aranake, Aniket Lee, Jin Gyu Knight, Doyle Cummings, Russell M. Cox, John Paul, Micah Byerley, Aaron R. Rutgers State Univ Dept Mech & Aerosp Engn Piscataway NJ 08854 USA Agcy Def Dev Taejon 305600 South Korea USAF Acad Dept Aeronaut Colorado Springs CO 80840 USA

An automated computational design optimization of a doubly offset (serpentine) subsonic diffuser is performed to assess the validity of a simple design principle for reducing flowfield distortion at the outlet. The design principle specifies that the flow be overexpanded within the bend, i.e., that the cross-sectional area in the bend exceed the cross-sectional area at the outlet. A baseline diffuser is defined as a monotonically increasing circular cross section following the specified doubly offset centerline. The design optimization uses a circular inlet and outlet that are identical to the baseline design, but permits a smooth blending of the cross section from circular to elliptical at the midpoint of the bend and returning to circular at the outlet while following the specified doubly offset centerline of the baseline design. The design variables of this study are the semimajor and semiminor axes of the ellipse at the midpoint. A commercial CAD program is used to loft the cross section smoothly from inlet to outlet. Turbulence is incorporated using a two-equation turbulence model. The automated computational design indicates that a substantial reduction in distortion is achieved by overexpanding the flow within the bend. Experimental evaluation of the baseline and optimal designs confirm an approximate 50% reduction in distortion coefficient for the optimal design compared with the baseline configuration, although the absolute values of the computed and experimental distortion coefficients differ.

关键词： Subsonic Diffusers Turbulence Models Vortex Generators CAD Software Flow Conditions multi objective genetic algorithm Numerical Simulation Wind Tunnels Mach Number Air Forces

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Aeronautic Conceptual Design Optimization Method Based on High-Order Singular Value Decomposition

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AIAA JOURNAL 2011年第12期49卷 2713-2725页

作者： de Lucas, S. Vega, J. M. Velazquez, A. Univ Politecn Madrid Aerosp Prop & Fluid Mech Dept Sch Aeronaut E-28040 Madrid Spain Univ Politecn Madrid Dept Appl Math Sch Aeronaut E-28040 Madrid Spain

An optimization method for conceptual design in aeronautics is presented that is based on a genetic algorithm. The various ingredients in the target function are calculated for each individual using surrogates of the associated technical disciplines that are constructed via high-order singular value decomposition and one-dimensional interpolation. These surrogates result from a limited number of computational fluid dynamics calculated snapshots. The resulting method is both flexible and much more computationally efficient than the conventional method based on direct calculation of the target function, especially if a large number of free design parameters and/or tunable modeling parameters are present. The method is illustrated considering a simplified version of the conceptual design of an aircraft empennage.

关键词： Singular Value Decomposition Aircraft Configurations CFD multi objective genetic algorithm Aeronautics Stability Derivatives Lift Coefficient Taper Ratio Torsion Box Sweep Angle

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Geometry Parameterization and Computational Mesh Deformation by Physics-Based Direct Manipulation Approaches

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AIAA JOURNAL 2010年第8期48卷 1817-1832页

作者： Yamazaki, Wataru Mouton, Sylvain Carrier, Gerald Off Natl Etud & Rech Aerosp Appl Aerodynam Dept F-92190 Meudon France Off Natl Etud & Rech Aerosp Appl Aerodynam Dept F-59045 Lille France

Consistent geometry parameterization of different models used in multidisciplinary optimization is one of the major issues for efficient design optimization. In this research, physics-based free-form deformation and radial-basis-function-based deformation approaches that allow a direct manipulation of an arbitrary object are proposed for efficient geometry manipulation and parameterization in the optimization processes. The developed methods can deform any computational mesh mapped on the deformable geometry at once. The methods have several advantages for geometry parameterization, such as easy handling of complex objects, direct manipulation, local controllability, and intuitive deformation as real elastic objects. In addition, they offer a straightforward solution for constructing a hierarchical/adaptive parameterization that can benefit the optimization algorithmic performances. Application to an aerodynamic design optimization showed that the methods were effective for efficient design optimization.

关键词： Aerodynamic Design Pilot Numerical Simulation Stiffness Matrices Wing Body Configuration Lagrange multipliers Poisson's Ratio Computer Graphics multi objective genetic algorithm Optimization algorithm

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Development of Fuzzy Muscle Contraction and Activation Model using multi-objective Optimisation

Development of Fuzzy Muscle Contraction and Activation Model...

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4th IEEE International Systems Conference

作者： Ibrahim, B. S. K. K. Tokhi, M. O. Gharooni, S. C. Huq, M. S. Univ Sheffield Dept Automat Control & Syst Engn Sheffield S Yorkshire England

ISBN: (纸本)9781424458837

Characterization of electrically stimulated muscle is complex because of the non-linearity and time-varying nature of the system with interdependent variables. The muscle model consists of relatively well known time-invariant passive properties and uncertain time-variant active properties. The objective of this study is to develop an active properties model that can be implemented in biomechanical models of the lower extremities, which are generally used for the simulation of joint movements such as walking and cycling, A new approach for dynamic characterization of active properties (combination of muscle contraction and activation) of the quadriceps muscle using fuzzy model by optimizing with multi objective genetic algorithm (MOGA) is presented. MOGA is used with two objectives;to minimize the prediction error to fit the experimental data and reduce the weighting factors of the fuzzy rules to minimize the complexity of the fuzzy model. The results show that the knee joint model developed gives an accurate dynamic characterization of active properties of the knee joint.

关键词： Knee joint functional electrical stimulation multi objective genetic algorithm fuzzy inference system

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Augmented Feedforward and Feedback Control of a Twin Rotor System Using Real-coded MOGA

Augmented Feedforward and Feedback Control of a Twin Rotor S...

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2010 IEEE World Congress on Computational Intelligence

作者： Toha, S. F. Tokhi, M. O. Univ Sheffield Dept Automat Control & Syst Engn Sheffield S1 3JD S Yorkshire England

ISBN: (纸本)9781424481262

Vibration suppression is crucial for applications in engineering particularly for aircraft systems. A hybrid control approach comprising a feedforward intelligent command shaping technique inverse-model based PID feedback control is presented in this paper. The proposed augmented control scheme is used to control both the flexible motion and rigid body dynamics of a twin rotor multi-input multi-optput system (TRMS). The advantage of using command shaping is to reduce system vibration. However, it can cause delay in system. Furthermore, performance requirements based on tracking error, rise time, settling time, percentage overshoot and steady state error are often found to be conflicting with one another in most flexible systems. Therefore real-coded multi objective genetic algorithm is employed in this work to compromise the problems and determine a set of solutions for the amplitudes and corresponding time locations of impulses on an extra sensitive (EI), four-impulse sequence command shaper as well as gain parameters for the PID controller. The effectiveness of the proposed technique is assessed both in the time domain and the frequency domain. Moreover, a comparative assessment of the performance of the technique with the system response and unshaped finite step input is presented.

关键词： Vibration suppression twin rotor system multi objective genetic algorithm

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Development of Fuzzy Muscle Contraction and Activation Model using multi-objective Optimisation

Development of Fuzzy Muscle Contraction and Activation Model...

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Annual IEEE International Systems Conference

作者： B. S. K. K. Ibrahim M. O. Tokhi S. C. Gharooni M. S. Huq Department of Automatic Control and System Engineering University of Sheffield

ISBN: (纸本)9781424458820

关键词： Knee joint Functional electrical stimulation multi objective genetic algorithm Fuzzy inference system Knee Joint Electric Stimulation fuzzy inference system Quadriceps Muscle fuzzy modeling Muscle Contraction joint mobilizations Error of prediction time varying Fuzzy

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