• Title/Summary/Keyword: Multi-variable optimization

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Efficient Optimization of the Suspension Characteristics Using Response Surface Model for Korean High Speed Train (반응표면모델을 이용한 한국형 고속전철 현가장치의 효율적인 최적설계)

  • Park, C.K.;Kim, Y.G.;Bae, D.S.;Park, T.W.
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.12 no.6
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    • pp.461-468
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    • 2002
  • Computer simulation is essential to design the suspension elements of railway vehicle. By computer simulation, engineers can assess the feasibility of the given design factors and change them to get a better design. But if one wishes to perform complex analysis on the simulation, such as railway vehicle dynamic, the computational time can become overwhelming. Therefore, many researchers have used a surrogate model that has a regression model performed on a data sampling of the simulation. In general, metamodels(surrogate model) take the form y($\chi$)=f($\chi$)+$\varepsilon$, where y($\chi$) is the true output, f($\chi$) is the metamodel output, and is the error. In this paper, a second order polynomial equation is used as the RSM(response surface model) for high speed train that have twenty-nine design variables and forty-six responses. After the RSM is constructed, multi-objective optimal solutions are achieved by using a nonlinear programming method called VMM(variable matric method) This paper shows that the RSM is a very efficient model to solve the complex optimization problem.

Minimization of wind load on setback tall building using multiobjective optimization procedure

  • Bairagi, Amlan Kumar;Dalui, Sujit Kumar
    • Wind and Structures
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    • v.35 no.3
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    • pp.157-175
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    • 2022
  • This paper highlights the minimization of drag and lift coefficient of different types both side setback tall buildings by the multi-objective optimization technique. The present study employed 48 number both-side setback models for simulation purposes. This study adopted three variables to find the two objective functions. Setback height and setback distances from the top of building models are considered variables. The setback distances are considered between 10-40% and setback heights are within 6-72% from the top of the models. Another variable is wind angles, which are considered from 0° to 90° at 15° intervals according to the symmetry of the building models. Drag and lift coefficients according to the different wind angles are employed as the objective functions. Therefore 336 number population data are used for each objective function. Optimum models are compared with computational simulation and found good agreements of drag and lift coefficient. The design wind angle variation of the optimum models is considered for drag and lift study on the main square model. The drag and lift data of the square model are compared with the optimum models and found the optimized models are minimizing the 45-65% drag and 25-60% lift compared to the initial square model.

Machinability investigation of gray cast iron in turning with ceramics and CBN tools: Modeling and optimization using desirability function approach

  • Boutheyna Gasmi;Boutheyna Gasmi;Septi Boucherit;Salim Chihaoui;Tarek Mabrouki
    • Structural Engineering and Mechanics
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    • v.86 no.1
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    • pp.119-137
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    • 2023
  • The purpose of this research is to assess the performance of CBN and ceramic tools during the dry turning of gray cast iron EN GJL-350. During the turning operation, the variable machining parameters are cutting speed, feed rate, depth of cut and type of the cutting material. This contribution consists of two sections, the first one deals with the performance evaluation of four materials in terms of evolution of flank wear, surface roughness (2D and 3D) and cutting forces. The focus of the second section is on statistical analysis, followed by modeling and optimization. The experiments are conducted according to the Taguchi design L32 and based on ANOVA approach to quantify the impact of input factors on the output parameters, namely, the surface roughness (Ra), the cutting force (Fz), the cutting power (Pc), specific cutting energy (Ecs). The RSM method was used to create prediction models of several technical factors (Ra, Fz, Pc, Ecs and MRR). Subsequently, the desirability function approach was used to achieve a multi-objective optimization that encompasses the output parameters simultaneously. The aim is to obtain optimal cutting regimes, following several cases of optimization often encountered in industry. The results found show that the CBN tool is the most efficient cutting material compared to the three ceramics. The optimal combination for the first case where the importance is the same for the different outputs is Vc=660 m/min, f=0.116 mm/rev, ap=0.232 mm and the material CBN. The optimization results have been verified by carrying out confirmation tests.

RIS Selection and Energy Efficiency Optimization for Irregular Distributed RIS-assisted Communication Systems

  • Xu Fangmin;Fu Jinzhao;Cao HaiYan;Hu ZhiRui
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.7
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    • pp.1823-1840
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    • 2023
  • In order to improve spectral efficiency and reduce power consumption for reconfigurable intelligent surface (RIS) assisted wireless communication systems, a joint design considering irregular RIS topology, RIS on-off switch, power allocation and phase adjustment is investigated in this paper. Firstly, a multi-dimensional variable joint optimization problem is established under multiple constraints, such as the minimum data requirement and power constraints, with the goal of maximizing the system energy efficiency. However, the proposed optimization problem is hard to be resolved due to its property of nonlinear nonconvex integer programming. Then, to tackle this issue, the problem is decomposed into four sub-problems: topology design, phase shift adjustment, power allocation and switch selection. In terms of topology design, Tabu search algorithm is introduced to select the components that play the main role. For RIS switch selection, greedy algorithm is used to turn off the RISs that play the secondary role. Finally, an iterative optimization algorithm with high data-rate and low power consumption is proposed. The simulation results show that the performance of the irregular RIS aided system with topology design and RIS selection is better than that of the fixed topology and the fix number of RISs. In addition, the proposed joint optimization algorithm can effectively improve the data rate and energy efficiency by changing the propagation environment.

Generation of Pareto Sets based on Resource Reduction for Multi-Objective Problems Involving Project Scheduling and Resource Leveling (프로젝트 일정과 자원 평준화를 포함한 다목적 최적화 문제에서 순차적 자원 감소에 기반한 파레토 집합의 생성)

  • Jeong, Woo-Jin;Park, Sung-Chul;Yim, Dong-Soon
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.43 no.2
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    • pp.79-86
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    • 2020
  • To make a satisfactory decision regarding project scheduling, a trade-off between the resource-related cost and project duration must be considered. A beneficial method for decision makers is to provide a number of alternative schedules of diverse project duration with minimum resource cost. In view of optimization, the alternative schedules are Pareto sets under multi-objective of project duration and resource cost. Assuming that resource cost is closely related to resource leveling, a heuristic algorithm for resource capacity reduction (HRCR) is developed in this study in order to generate the Pareto sets efficiently. The heuristic is based on the fact that resource leveling can be improved by systematically reducing the resource capacity. Once the reduced resource capacity is given, a schedule with minimum project duration can be obtained by solving a resource-constrained project scheduling problem. In HRCR, VNS (Variable Neighborhood Search) is implemented to solve the resource-constrained project scheduling problem. Extensive experiments to evaluate the HRCR performance are accomplished with standard benchmarking data sets, PSPLIB. Considering 5 resource leveling objective functions, it is shown that HRCR outperforms well-known multi-objective optimization algorithm, SPEA2 (Strength Pareto Evolutionary Algorithm-2), in generating dominant Pareto sets. The number of approximate Pareto optimal also can be extended by modifying weight parameter to reduce resource capacity in HRCR.

Fuzzy Control of Smart TMD using Multi-Objective Genetic Algorithm (다목적 유전자알고리즘을 이용한 스마트 TMD의 퍼지제어)

  • Kang, Joo-Won;Kim, Hyun-Su
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.24 no.1
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    • pp.69-78
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    • 2011
  • In this study, an optimization method using multi-objective genetic algorithm(MOGA) has been proposed to develop a fuzzy control algorithm that can effectively control a smart tuned mass damper(TMD). A 76-story benchmark building subjected to wind load was selected as an example structure. The smart TMD consists of 100kN MR damper and the natural period of the smart TMD was tuned to the first mode natural period of the example structure. Damping force of MR damper is controlled to reduce the wind-induced responses of the example structure by a fuzzy logic controller. Two input variables of the fuzzy logic controller are the acceleration of 75th floor and the displacement of the smart TMD and the output variable is the command voltage sent to MR damper. Multi-objective genetic algorithm(NSGA-II) was used for optimization of the fuzzy logic controller and the acceleration of 75th story and the displacement of the smart TMD were used as objective function. After optimization, a series of fuzzy logic controllers which could appropriately reduce both wind responses of the building and smart TMD were obtained. Based on numerical results, it has been shown that the control performance of the smart TMD is much better than that of the passive TMD and it is even better than that of the sample active TMD in some cases.

Implementation of Feedback Controller on the Servo System (교류서보계의 궤환제어 구현)

  • Chun, Sam-Suk;Park, Chan-Won
    • Proceedings of the KIEE Conference
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    • 2006.07b
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    • pp.719-720
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    • 2006
  • In the mechanical system, optimization of motion control is very essential in the aspect of automation technique progress. In the servo system, the function of controller is very important but most of the controllers have played only the role of pulse generator because the controller with main function is very expensive. In this thesis, the system was composed of PC, commonly used driver AC servo motor and a produced control board. The PC transmit a gain, a locus data to a driver and controller. At the same time, it converts imformation from the controller and convert them into data and offer an output with graph. The role of a controller is to trasmit a locus data to a driver and counting the pulse on the phase of an encoder to the PC. We have performed the experiment in order to confirm with variable PID parameter capable of the optimization of gain tuning with the counting of feedback control sensor signal with regard to the external interface into the system, such as torque. Based on the experiment result, we have confirmed as follows: First, it was confirmed that we could easily input control factors P.I Gain, constant $K_P,\;K_I$ into PC. Second, not only pulse generator function was possible, but with this pulse it was also possible to count using software with PIC chip. And third, using the multi-purpose PIC micro chip, simple operation and the formation of small size AC Servo Controller was possible.

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Performance Optimization of High Specific Speed Pump-Turbines by Means of Numerical Flow Simulation (CFD) and Model Testing

  • Kerschberger, Peter;Gehrer, Arno
    • International Journal of Fluid Machinery and Systems
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    • v.3 no.4
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    • pp.352-359
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    • 2010
  • In recent years, the market has shown increasing interest in pump-turbines. The prompt availability of pumped storage plants and the benefits to the power system achieved by peak lopping, providing reserve capacity, and rapid response in frequency control are providing a growing advantage. In this context, there is a need to develop pumpturbines that can reliably withstand dynamic operation modes, fast changes of discharge rate by adjusting the variable diffuser vanes, as well as fast changes from pumping to turbine operation. In the first part of the present study, various flow patterns linked to operation of a pump-turbine system are discussed. In this context, pump and turbine modes are presented separately and different load cases are shown in each operating mode. In order to create modern, competitive pump-turbine designs, this study further explains what design challenges should be considered in defining the geometry of a pump-turbine impeller. The second part of the paper describes an innovative, staggered approach to impeller development, applied to a low head pump-turbine project. The first level of the process consists of optimization strategies based on evolutionary algorithms together with 3D in-viscid flow analysis. In the next stage, the hydraulic behavior of both pump mode and turbine mode is evaluated by solving the full 3D Navier-Stokes equations in combination with a robust turbulence model. Finally, the progress in hydraulic design is demonstrated by model test results that show a significant improvement in hydraulic performance compared to an existing reference design.

Hybrid genetic-paired-permutation algorithm for improved VLSI placement

  • Ignatyev, Vladimir V.;Kovalev, Andrey V.;Spiridonov, Oleg B.;Kureychik, Viktor M.;Ignatyeva, Alexandra S.;Safronenkova, Irina B.
    • ETRI Journal
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    • v.43 no.2
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    • pp.260-271
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    • 2021
  • This paper addresses Very large-scale integration (VLSI) placement optimization, which is important because of the rapid development of VLSI design technologies. The goal of this study is to develop a hybrid algorithm for VLSI placement. The proposed algorithm includes a sequential combination of a genetic algorithm and an evolutionary algorithm. It is commonly known that local search algorithms, such as random forest, hill climbing, and variable neighborhoods, can be effectively applied to NP-hard problem-solving. They provide improved solutions, which are obtained after a global search. The scientific novelty of this research is based on the development of systems, principles, and methods for creating a hybrid (combined) placement algorithm. The principal difference in the proposed algorithm is that it obtains a set of alternative solutions in parallel and then selects the best one. Nonstandard genetic operators, based on problem knowledge, are used in the proposed algorithm. An investigational study shows an objective-function improvement of 13%. The time complexity of the hybrid placement algorithm is O(N2).

Shape Optimization of Impeller Blades for Bidirectional Axial Flow Pump (양방향 축류펌프용 임펠러 블레이드의 형상최적설계)

  • Baek, Seok Heum;Jung, Won Hyuk;Kang, Sangmo
    • Transactions of the Korean Society of Mechanical Engineers B
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    • v.36 no.12
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    • pp.1141-1150
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    • 2012
  • This paper describes the shape optimization of impeller blades for an anti-heeling bidirectional axial flow pump used in ships. In general, a bidirectional axial pump has efficiency much lower than that of a classical unidirectional pump because of the symmetry of the blade type. In this study, by focusing on a pump impeller, the shape of the blades is redesigned to develop a bidirectional axial pump with higher efficiency. The commercial code employed in this simulation is CFX v.13. The CFD result of the pump torque, head, and hydraulic efficiency was compared. The orthogonal array (OA) and analysis of variance (ANOVA) techniques and surrogate-model-based optimization using orthogonal polynomials are employed to determine the main effects and their optimal design variables. According to the optimal design, we confirm an effective design variable for impeller blades and explain the optimal solution as well as the usefulness of satisfying the constraints of the pump torque and head.