• 제목/요약/키워드: single objective optimization

검색결과 221건 처리시간 0.031초

DESIGN OF SINGLE-SIDED LINEAR INDUCTION MOTOR USING FINITE ELEMENT METHOD AND SUMT (유한요소법과 SUMT를 이용한 편측식 선형유도전동기의 설계)

  • Im, Dal-Ho;Kim, Hak-Ryun;Lee, Cheol-Jik;Park, Seung-Chan
    • Proceedings of the KIEE Conference
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    • 대한전기학회 1992년도 하계학술대회 논문집 A
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    • pp.503-505
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    • 1992
  • This paper describes the optimization of design variables of SLIM using finite element method and SUMT(Sequential Unconstrained Minimization Technique). Thrust is taken as an objective function in order to maximize thrust under constant current drive, and seven independent design variables and nine constraints are chosen. As a result, $\tau$/g(pole pitch/airgap) and $\tau$/$d_{AL}$(pole pitch/aluminum depth) of good criteria in SLIM design are determined.

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Inventory control for the item with multiple demand classes

  • Seo, Jungwon
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 대한산업공학회/한국경영과학회 1994년도 춘계공동학술대회논문집; 창원대학교; 08월 09일 Apr. 1994
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    • pp.427-431
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    • 1994
  • The objective of this paper is to provide an inventory control policy for the system that carries a single item with a multiple demand classes, when the demand is Poisson distributed random variable. The inventory control process includes the process of determining the reorder point, and the process of inventory control during the lead time. The goal of the optimization process is to achieve the service level of each demand class as well as the system-wide total service level at a preset desired service level while sustaining a minimum average inventory.

A Method for Design of Discrete Variable Stochastic Systems using Simulation (이산형 변수 시스템의 설계를 위한 시뮬레이션 활용 기법 연구)

  • 박경종
    • Journal of the Korea Society for Simulation
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    • 제8권3호
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    • pp.1-16
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    • 1999
  • This paper deals with a discrete simulation optimization method for designing a complex probabilistic discrete event system. The proposed algorithm in this paper searches the effective and reliable alternatives satisfying the target values of the system to be designed through a single run in a relatively short time period. It tries to estimate an autoregressive model, and construct mean and confidence interval for evaluating correctly the objective function obtained by small amount of output data. The experimental results using the proposed method are also shown.

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A Study on Multi-Objective Fuzzy Optimum Design of Truss Structures

  • Mu, Zai-Gen;Ge, Xin;Yan, Mou;Chen, Yun-Zhou
    • Journal of Korean Association for Spatial Structures
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    • 제3권2호
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    • pp.77-83
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    • 2003
  • This paper presents decision making method of structural multi-objective fuzzy optimum problem. The data and behavior of many engineering systems are not know precisely and the designer is required to design the system in the presence of fuzziness in the multi-goals, constraints and consequences of possible actions. In this paper, in order to find a satisfactory solution, the membership functions are constructed for the fuzzy objectives subject to the fuzzy constraints, and two approaches are presented by using the different types of fuzzy decision making. Thus, multi-objective fuzzy optimum problem can be converted into single objective non-fuzzy optimum problem and satisfactory solution of the multi-objective fuzzy optimum problem can be found with general optimum programming. Illustrative numerical example of the ten bar truss for minimum weight and minimum deflection is provided to demonstrate the process of finding the solution and the results are discussed.

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A Study on Radio Resource Management for Multi-cell SC-FDMA Systems (다중셀 SC-FDMA를 위한 무선자원 관리기법에 관한연구)

  • Chung, Yong-Joo
    • Journal of Korea Society of Industrial Information Systems
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    • 제15권4호
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    • pp.7-15
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    • 2010
  • This study proposes a rad o resource management scheme to maximize the performance of the LTE(Long Term Evolution) uplink, using SC-FDMA(Single Carrier-Frequency Division Multiple Access). Rather than the single-cell SC-FDMA system the existing studies are mainly concerning, this study focuses on multi-cell system which needs considering the interaction among cells. Radio resource management is divided into two phases, planning and operation phases. The former is for the master eNB(e-NodeB) to allocate RBs(radio bearer) to eNB, the latter for eNB to assign RBs to the mobiles in the cell. For each phase, an optimization model and greedy algorithm are proposed. Optimization models aim to maximize the system performance while satisfying the constraints for both QoS and RB continuity. The greedy algorithms, like generic ones, move from a solution to a neighboring one having the best objective value among neighboring ones. From the numerous numerical experiments, the performance and characteristics of the algorithms are analyzed. This study is expected to play a volunteering role in radio resource management for the multi-cell SC-FDMA system.

Design Optimization of Composite Radar Absorbing Structures to Improve Stealth Performance

  • Jang, Byungwook;Kim, Myungjun;Park, Jungsun;Lee, Sooyong
    • International Journal of Aeronautical and Space Sciences
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    • 제17권1호
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    • pp.20-28
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    • 2016
  • In this study, an efficient method of designing laminate composite radar absorbing structures (RAS) is proposed with consideration given to the structural shape so as to improve aircraft stealth performance. The calculation of the radar cross section (RCS) should be decreased to enhance the efficiency of the stochastic optimization when designing an RAS. In the proposed method, RAS are optimized to match up the input impedance of the minimal RCS, which is obtained by using physical optics and the transmission line theory. Single and double layer dielectric RAS for aircraft wings are employed as numerical examples and designed using the proposed method, RCS minimization and reflection coefficient minimization. The availability of the proposed method is assessed by comparing the similarity of the results and computation time with other design methods. According to the results, the proposed method produces the same results as the stochastic optimization, which adopts the RCS as the objective function, and can improve RAS design efficiency by reducing the number of RCS analyses.

Study on Integrated Workflow for Designing Sustainable Tall Building - With Parametric method using Rhino Grasshopper and DIVA for Daylight Optimization

  • Kim, Hyeong-ill
    • KIEAE Journal
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    • 제16권5호
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    • pp.21-28
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    • 2016
  • Purpose: The Objective of this study is to explore the capabilities of an integrated modelling and simulation workflow when applied to an experiment-based research process, aimed at deriving daylight optimization strategies specific to tall buildings. Methods: Two methods were devised to apply this workflow with the help of DIVA and Rhino/Grasshopper. The first method is a multiple variant analysis by setting up an appropriate base case and analysing its daylight and energy performance, forming the basis of comparison for subsequent cases for design variants. The second method involved setting up the base case within a site context and conducting a solar irradiation study. An architectural variables such as overhang and shading device, were then defined as inputs in the parametric definition in Grasshopper to control the selected variable. Results: While the first method took advantage of the speed and efficiency of the integrated workflow, the second method was derived based on the ability to directly process simulation data within the integrated, single-software platform of the proposed workflow. Through these methods, different architectural strategies were explored, both to increase daylight penetration and to reduce radiant heat gain. The focus is on methods by which this workflow can be applied to facilitate the experimental derivation of daylight optimization strategies that are specific to tall building design.

Finite element model updating of a cable-stayed bridge using metaheuristic algorithms combined with Morris method for sensitivity analysis

  • Ho, Long V.;Khatir, Samir;Roeck, Guido D.;Bui-Tien, Thanh;Wahab, Magd Abdel
    • Smart Structures and Systems
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    • 제26권4호
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    • pp.451-468
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    • 2020
  • Although model updating has been widely applied using a specific optimization algorithm with a single objective function using frequencies, mode shapes or frequency response functions, there are few studies that investigate hybrid optimization algorithms for real structures. Many of them did not take into account the sensitivity of the updating parameters to the model outputs. Therefore, in this paper, optimization algorithms and sensitivity analysis are applied for model updating of a real cable-stayed bridge, i.e., the Kien bridge in Vietnam, based on experimental data. First, a global sensitivity analysis using Morris method is employed to find out the most sensitive parameters among twenty surveyed parameters based on the outputs of a Finite Element (FE) model. Then, an objective function related to the differences between frequencies, and mode shapes by means of MAC, COMAC and eCOMAC indices, is introduced. Three metaheuristic algorithms, namely Gravitational Search Algorithm (GSA), Particle Swarm Optimization algorithm (PSO) and hybrid PSOGSA algorithm, are applied to minimize the difference between simulation and experimental results. A laboratory pipe and Kien bridge are used to validate the proposed approach. Efficiency and reliability of the proposed algorithms are investigated by comparing their convergence rate, computational time, errors in frequencies and mode shapes with experimental data. From the results, PSO and PSOGSA show good performance and are suitable for complex and time-consuming analysis such as model updating of a real cable-stayed bridge. Meanwhile, GSA shows a slow convergence for the same number of population and iterations as PSO and PSOGSA.

An interactive and iterative control panel layout

  • 박성준;정의승;조항준
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 대한산업공학회/한국경영과학회 1994년도 춘계공동학술대회논문집; 창원대학교; 08월 09일 Apr. 1994
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    • pp.103-111
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    • 1994
  • An interactive and iterative design method based on the constraint satisfaction problem (CSP) technique was developed to generate an ergonomically sound layout of a control panel. This control panel layout method attempts to incorporate a variety of relevant ergonomic principles and design constraints, and generate an optimal or, at least, a "satisfactory" solution through iterative interactions with the designer. The existing panel design and layout methods are mostly based on the optimization of single objective function formulated to reflect and trade off all ergonomic design objectives which are largely different in their nature. In fact, the problem of seeking an ergonomically sound panel design should be viewed as a multiple objective optimization problem. Furthermore, most of the design objectives should be understood as constraints rather than objectives to be optimized. Hence, a constraint satisfaction approach is proposed in this study as a framework for the panel designer to search through the design decision space effectively and make various design decisions iteratively. In order to apply the constraint satisfaction approach to the panel design procedure, the ergonomic principles such as frequency-of-use, importance, functional grouping, and sequence-of-use are formalized as CSP terms. With this formalization, a prototype system was implemented and applied to panel layout problems. The results clearly showed the effectiveness of the proposed approach since it permits designers to consider and iteratively evaluate various design constraints and ergonomic principles, and, therefore, aids the panel designer to come up with an ergonomically sound control panel layout.

Decision Variable Design of Discrete Systems using Simulation Optimization (시뮬레이션 최적화를 이용한 이산형 시스템의 결정변수 설계)

  • 박경종
    • Proceedings of the Korea Society for Simulation Conference
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    • 한국시뮬레이션학회 1999년도 추계학술대회 논문집
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    • pp.63-69
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    • 1999
  • The research trend of the simulation optimization has been focused on exploring continuous decision variables. Yet, the research in discrete decision variable area has not been fully studied. A new research trend for optimizing discrete decision variables ha just appeared recently. This study, therefore, deals with a discrete simulation method to get the system evaluation criteria required for designing a complex probabilistic discrete event system and to search the effective and reliable alternatives to satisfy the objective values of the given system through a on-line, single run with the short time period. Finding the alternative, we construct an algorithm which changes values of decision variables and a design alternative by using the stopping algorithm which ends the simulation in a steady state of system. To avoid the loss of data while analyzing the acquired design alternative in the steady state, we provide background for estimation of an auto-regressive model and mean and confidence interval for evaluating correctly the objective function obtained by small amount of output data through simulation with the short time period. In numerical experiment we applied the proposed algorithm to (s, S) inventory system problem with varying Δt value. In case of the (s, S) inventory system, we obtained good design alternative when Δt value is larger than 100.

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