• Title/Summary/Keyword: Multi-objective Optimization Problem

Search Result 309, Processing Time 0.025 seconds

Information entropy based algorithm of sensor placement optimization for structural damage detection

  • Ye, S.Q.;Ni, Y.Q.
    • Smart Structures and Systems
    • /
    • v.10 no.4_5
    • /
    • pp.443-458
    • /
    • 2012
  • The structural health monitoring (SHM) benchmark study on optimal sensor placement problem for the instrumented Canton Tower has been launched. It follows the success of the modal identification and model updating for the Canton Tower in the previous benchmark study, and focuses on the optimal placement of vibration sensors (accelerometers) in the interest of bettering the SHM system. In this paper, the sensor placement problem for the Canton Tower and the benchmark model for this study are first detailed. Then an information entropy based sensor placement method with the purpose of damage detection is proposed and applied to the benchmark problem. The procedure that will be implemented for structural damage detection using the data obtained from the optimal sensor placement strategy is introduced and the information on structural damage is specified. The information entropy based method is applied to measure the uncertainties throughout the damage detection process with the use of the obtained data. Accordingly, a multi-objective optimal problem in terms of sensor placement is formulated. The optimal solution is determined as the one that provides equally most informative data for all objectives, and thus the data obtained is most informative for structural damage detection. To validate the effectiveness of the optimally determined sensor placement, damage detection is performed on different damage scenarios of the benchmark model using the noise-free and noise-corrupted measured information, respectively. The results show that in comparison with the existing in-service sensor deployment on the structure, the optimally determined one is capable of further enhancing the capability of damage detection.

Approximate Multi-Objective Optimization of A Wall-mounted Monitor Bracket Arm Considering Strength Design Conditions (강도조건을 고려한 벽걸이 모니터 브라켓 암의 다중목적 근사최적설계)

  • Doh, Jaehyeok;Lee, Jongsoo
    • Transactions of the Korean Society of Mechanical Engineers A
    • /
    • v.39 no.5
    • /
    • pp.535-541
    • /
    • 2015
  • In this study, an approximate multi-objective optimization of a wall-mounted monitor bracket arm was performed. The rotation angle of the bracket arm was determined considering the inplane degree of freedom. We then formulated an optimization problem on maximum stress and deflection. Analyses of mean and design parameters were conducted for sensitivity regarding performance with orthogonal array and response surface method (RSM). RSM models of objective and constraint functions were generated using central composite (CCD) and D-optimal design. The accuracy of approximate models was evaluated through $R^2$ value. The obtained optimal solutions by non-dominant sorting genetic algorithm (NSGA-II) were validated through the finite element analysis and we compared the obtained optimal solution by CCD and D-optimal design.

Damage detection based on MCSS and PSO using modal data

  • Kaveh, Ali;Maniat, Mohsen
    • Smart Structures and Systems
    • /
    • v.15 no.5
    • /
    • pp.1253-1270
    • /
    • 2015
  • In this paper Magnetic Charged System Search (MCSS) and Particle Swarm Optimization (PSO) are applied to the problem of damage detection using frequencies and mode shapes of the structures. The objective is to identify the location and extent of multi-damage in structures. Both natural frequencies and mode shapes are used to form the required objective function. To moderate the effect of noise on measured data, a penalty approach is applied. A variety of numerical examples including two beams and two trusses are considered. A comparison between the PSO and MCSS is conducted to show the efficiency of the MCSS in finding the global optimum. The results show that the present methodology can reliably identify damage scenarios using noisy measurements and incomplete data.

Electrode Shape Optimization of Piezo Sensors Using Genetic Algorithm (유전 알고리듬을 이용한 압전센서의 전극형상 최적화)

  • Lee Ki-Moon;Park Hyun-Chul;Park Chul-Hue
    • Transactions of the Korean Society of Mechanical Engineers A
    • /
    • v.30 no.6 s.249
    • /
    • pp.698-704
    • /
    • 2006
  • This paper presents an electrode shape design method for the multi-mode sensors that could deteict the selected structural multiple modes. The structure used for this study is an isotropic cantilever beam type with a PVDF (polyvinylidene fluoride) which is bonded onto the structure as a sensor. The shape optimization problem is solved by using Genetic Algorithm (GA) with an appropriate objective function. The performance of analytical optimal shape sensor is compared with that of experimental work. The results show that the, obtained electrode shape sensors have good performance to detect the multiple vibration modes simultaneously.

Throughput maximization for underlay CR multicarrier NOMA network with cooperative communication

  • Manimekalai, Thirunavukkarasu;Joan, Sparjan Romera;Laxmikandan, Thangavelu
    • ETRI Journal
    • /
    • v.42 no.6
    • /
    • pp.846-858
    • /
    • 2020
  • The non-orthogonal multiple access (NOMA) technique offers throughput improvement to meet the demands of the future generation of wireless communication networks. The objective of this work is to further improve the throughput by including an underlay cognitive radio network with an existing multi-carrier NOMA network, using cooperative communication. The throughput is maximized by optimal resource allocation, namely, power allocation, subcarrier assignment, relay selection, user pairing, and subcarrier pairing. Optimal power allocation to the primary and secondary users is accomplished in a way that target rate constraints of the primary users are not affected. The throughput maximization is a combinatorial optimization problem, and the computational complexity increases as the number of users and/or subcarriers in the network increases. To this end, to reduce the computational complexity, a dynamic network resource allocation algorithm is proposed for combinatorial optimization. The simulation results show that the proposed network improves the throughput.

Robust Predictive Feedback Control for Constrained Systems

  • Giovanini, Leonardo;Grimble, Michael
    • International Journal of Control, Automation, and Systems
    • /
    • v.2 no.4
    • /
    • pp.407-422
    • /
    • 2004
  • A new method for the design of predictive controllers for SISO systems is presented. The proposed technique allows uncertainties and constraints to be concluded in the design of the control law. The goal is to design, at each sample instant, a predictive feedback control law that minimizes a performance measure and guarantees of constraints are satisfied for a set of models that describes the system to be controlled. The predictive controller consists of a finite horizon parametric-optimization problem with an additional constraint over the manipulated variable behavior. This is an end-constraint based approach that ensures the exponential stability of the closed-loop system. The inclusion of this additional constraint, in the on-line optimization algorithm, enables robust stability properties to be demonstrated for the closed-loop system. This is the case even though constraints and disturbances are present. Finally, simulation results are presented using a nonlinear continuous stirred tank reactor model.

유연성과 강성을 고려한 최적구조설계

  • Min, Seungjae;Nishiwaki, Shinji;Kikuchi, Noboru
    • Transactions of the Korean Society of Mechanical Engineers A
    • /
    • v.21 no.9
    • /
    • pp.1432-1440
    • /
    • 1997
  • The flexibility as well as the stiffness is required to perform mechanical function of a structure such as compliant mechanisms, which can be applied to MEMS(Micro-Electro-Mechanical Systems), flexible manufacturing devices, and design for no assembly. In this paper, the optimal design problem to achieve both structural flexibility and stiffness is formulated using multi-objective function, and the optimization problem is resolved by using Finite Element Method(FEM) and Sequential Linear Programming(SLP). Design examples of compliant mechanisms are presented to validate the design method.

Freight and Fleet Optimization Models under CVO Environment (CVO 환경을 고려한 차량 및 화물 운송 최적 모델)

  • Choe Gyeong-Hyeon;Pyeon Je-Beom;Gwak Ho-Man
    • Proceedings of the Society of Korea Industrial and System Engineering Conference
    • /
    • 2002.05a
    • /
    • pp.209-215
    • /
    • 2002
  • In this paper, we propose a freight and fleet optimization model under CVO environment. The model is a kind of multi commodity network flow model based on Vehicle Routing Problem(VRP) and Vehicle Scheduling Problem(VSP), and considering operations and purposes of CVO. The main purpose of CVO is the freight and fleet management to reduce logistics cost and to Improve in vehicle safety. Thus, the objective of this model is to minimize routing cost of all the vehicle and to find the location of commodities which have origin and destination. We also present some computing test results.

  • PDF

Service Composition Based on Niching Particle Swarm Optimization in Service Overlay Networks

  • Liao, Jianxin;Liu, Yang;Wang, Jingyu;Zhu, Xiaomin
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • v.6 no.4
    • /
    • pp.1106-1127
    • /
    • 2012
  • Service oriented architecture (SOA) lends itself to model the application components to coarse-grained services in such a way that the composition of different services could be feasible. Service composition fulfills numerous service requirements by constructing composite applications with various services. As it is the case in many real-world applications, different users have diverse QoS demands issuing for composite applications. In this paper, we present a service composition framework for a typical service overlay network (SON) considering both multiple QoS constraints and load balancing factors. Moreover, a service selection algorithm based on niching technique and particle swarm optimization (PSO) is proposed for the service composition problem. It supports optimization problems with multiple constraints and objective functions, whether linear or nonlinear. Simulation results show that the proposed algorithm results in an acceptable level of efficiency regarding the service composition objective under different circumstances.

The Optimization of Bank Branches Efficiency by Means of Response Surface Method and Data Envelopment Analysis: A Case of Iran

  • Shadkam, Elham;Bijari, Mehdi
    • The Journal of Asian Finance, Economics and Business
    • /
    • v.2 no.2
    • /
    • pp.13-18
    • /
    • 2015
  • In this paper the DRC model is presented for solving multi objective problem. The proposed model is a combination of data envelopment analysis, Cuckoo algorithm and the response surface method. Due to reasons like costs, time and irreversible damages, it is not possible to analyze each and every one of the proposed models in practice, so the simulation is used. Since the number of experiments for simulation process is high then the optimization has gone to practice and directs the simulation process. The response surface method is used as one of the approaches of simulation optimization. Furthermore, data envelopment analysis is used to consider several response surfaces as efficiency response surface. Then this efficiency response surface is solved by Cuckoo algorithms. The main advantage of DRC model is to make one efficiency response surface function instate of multi surface function for every output and also using the advantages of Cuckoo algorithms. In order to demonstrate the effectiveness of the proposed approach, the branches of Refah bank in Mashhad is analyzed and the results are presented.