• Title/Summary/Keyword: Optimization approach study

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A New Hybrid Strategy for the Optimization of Xhemical Processing System

  • Cho, In-Ho;Yoon, En-Sup
    • 제어로봇시스템학회:학술대회논문집
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    • 1989.10a
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    • pp.848-855
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    • 1989
  • By structural comparison of process optimization strategies based on Simultaneous Modular Approach, they can be classified into two groups : the Sequential Module Based Approach and the Two-Tier Approach. The Sequential Module Based Approach needs rigorous models and a set of accurate solutions are guranteed. However, it requires large amount of computation time. In the Two-Tier Approach composed of rigorous and simplified models, optimization calculation uses simplified models, therefore comparatively smaller amount of computation time is required but the obtained solutions may not be accurate. These optimization problems were somewhat improved by the alternate application of the two strategies. In this study, improved optimization strategy is suggested, in which Jacobian Matrix is modified to accomodate the strong points of above mentioned strategies. The results of case study show that this approach is superior to the other strategies.

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An Empirical Data Driven Optimization Approach By Simulating Human Learning Processes (인간의 학습과정 시뮬레이션에 의한 경험적 데이터를 이용한 최적화 방법)

  • Kim Jinhwa
    • Journal of the Korean Operations Research and Management Science Society
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    • v.29 no.4
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    • pp.117-134
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    • 2004
  • This study suggests a data driven optimization approach, which simulates the models of human learning processes from cognitive sciences. It shows how the human learning processes can be simulated and applied to solving combinatorial optimization problems. The main advantage of using this method is in applying it into problems, which are very difficult to simulate. 'Undecidable' problems are considered as best possible application areas for this suggested approach. The concept of an 'undecidable' problem is redefined. The learning models in human learning and decision-making related to combinatorial optimization in cognitive and neural sciences are designed, simulated, and implemented to solve an optimization problem. We call this approach 'SLO : simulated learning for optimization.' Two different versions of SLO have been designed: SLO with position & link matrix, and SLO with decomposition algorithm. The methods are tested for traveling salespersons problems to show how these approaches derive new solution empirically. The tests show that simulated learning for optimization produces new solutions with better performance empirically. Its performance, compared to other hill-climbing type methods, is relatively good.

A Study on the Multidisciplinary Design Optimization Using Collaborative Optimization Approach (협동 최적화 접근 방법에 의한 타분야 최적 설계에 관한 연구)

  • 노명일;이규열
    • Korean Journal of Computational Design and Engineering
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    • v.5 no.3
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    • pp.263-275
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    • 2000
  • Multidisciplinary design optimization(MDO) can yield optimal design considering all the disciplinary requirements concurrently. A method to implement the collaborative optimization(CO) approach, one of the MDO methodologies, is developed using a pre-compiler “EzpreCompiler”, a design optimization library “EzOptimizer”, and a common object request broker architecture(CORBA) in distributed computing environment. The CO approach is applied to a mathematical example to show its applicability and equivalence to standard optimization(SO) formulation. In a realistic engineering problem such as optimal design of a two-member hub frame, optimal design of a speed reducer and initial design of a bulk carrier, the CO yields better results than the SO. Furthermore, the CO allows the distributed processing using the CORBA, which leads to reduction of overall computation time.

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Optimum Life-Cycle Cost Design of Steel Box Girder Bridges Using Collaborative Optimization (협동 최적화 방법을 이용한 강상자형교의 생애주기비용 최적설계)

  • 조효남;민대홍;권우성
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 2001.10a
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    • pp.201-210
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    • 2001
  • In this study, large-scale distributed design approach for a life cycle cost (LCC) optimization of steel box girder bridges was implemented. A collaborative optimization approach is one of the multidisciplinary design optimization approaches and it has been proven to be best suited for distributed design environment. The problem of optimum LCC design of steel box girder bridges is formulated as that of minimization of the expected total LCC that consists of initial cost maintenance cost expected retrofit costs for strength, deflection and crack. To discuss the possibility of the application for the collaborative optimization of steel box girder bridges, the results of this algorithm are compared with those of single level algorithm. From the numerical investigations, the collaborative optimization approach proposed in this study may be expected to be new concepts and design methodologies associated with the LCC approach.

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Optimizing Food Processing through a New Approach to Response Surface Methodology

  • Sungsue Rheem
    • Food Science of Animal Resources
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    • v.43 no.2
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    • pp.374-381
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    • 2023
  • In a previous study, 'response surface methodology (RSM) using a fullest balanced model' was proposed to improve the optimization of food processing when a standard second-order model has a significant lack of fit. However, that methodology can be used when each factor of the experimental design has five levels. In response surface experiments for optimization, not only five-level designs, but also three-level designs are used. Therefore, the present study aimed to improve the optimization of food processing when the experimental factors have three levels through a new approach to RSM. This approach employs three-step modeling based on a second-order model, a balanced higher-order model, and a balanced highest-order model. The dataset from the experimental data in a three-level, two-factor central composite design in a previous research was used to illustrate three-step modeling and the subsequent optimization. The proposed approach to RSM predicted improved results of optimization, which are different from the predicted optimization results in the previous research.

Reliability-Based Shape Optimization Under the Stress Constraints (응력 제한조건하의 신뢰성 기반 형상 최적설계)

  • Oh, Young-Kyu;Park, Jae-Yong;Im, Min-Gyu;Park, Jae-Yong;Han, Seog-Young
    • Journal of the Korean Society of Manufacturing Technology Engineers
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    • v.19 no.4
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    • pp.469-475
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    • 2010
  • The objective of this study is to integrate reliability analysis into shape optimization problem using the evolutionary structural optimization (ESO) in the application example. Reliability-based shape optimization is formulated as volume minimization problem with probabilistic stress constraint under minimization max. von Mises stress and allow stress. Young's modulus, external load and thickness are considered as uncertain variables. In order to compute reliability index, four methods, i.e., reliability index approach (RIA), performance measure approach (PMA), single-loop singlevector (SLSV) and adaptive-loop (ADL), are used. Reliability-based shape optimization design process is conducted to obtain optimal shape satisfying max. von Mises stress and reliability index constraints with the above four methods, and then each result is compared with respect to numerical stability and computing time.

Cross-Layer and End-to-End Optimization for the Integrated Wireless and Wireline Network

  • Gong, Seong-Lyong;Roh, Hee-Tae;Lee, Jang-Won
    • Journal of Communications and Networks
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    • v.14 no.5
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    • pp.554-565
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    • 2012
  • In this paper, we study a cross-layer and end-to-end optimization problem for the integrated wireless and wireline network that consists of one wireline core network and multiple wireless access networks. We consider joint end-to-end flow control/distribution at the transport and network layers and opportunistic scheduling at the data link and physical layers. We formulate a single stochastic optimization problem and solve it by using a dual approach and a stochastic sub-gradient algorithm. The developed algorithm can be implemented in a distributed way, vertically among communication layers and horizontally among all entities in the network, clearly showing what should be done at each layer and each entity and what parameters should be exchanged between layers and between entities. Numerical results show that our cross-layer and end-to-end optimization approach provides more efficient resource allocation than the conventional layered and separated optimization approach.

Optimization of trusses under uncertainties with harmony search

  • Togan, Vedat;Daloglu, Ayse T.;Karadeniz, Halil
    • Structural Engineering and Mechanics
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    • v.37 no.5
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    • pp.543-560
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    • 2011
  • In structural engineering there are randomness inherently exist on determination of the loads, strength, geometry, and so on, and the manufacturing of the structural members, workmanship etc. Thus, objective and constraint functions of the optimization problem are functions that depend on those randomly natured components. The constraints being the function of the random variables are evaluated by using reliability index or performance measure approaches in the optimization process. In this study, the minimum weight of a space truss is obtained under the uncertainties on the load, material and cross-section areas with harmony search using reliability index and performance measure approaches. Consequently, optimization algorithm produces the same result when both the approaches converge. Performance measure approach, however, is more efficient compare to reliability index approach in terms of the convergence rate and iterations needed.

A Study on Feedrate Optimization System for Cutting Force Optimization (절삭력 최적화를 위한 이송속도 제어 시스템에 관한 연구)

  • 김성진;정영훈;조동우
    • Proceedings of the Korean Society of Machine Tool Engineers Conference
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    • 2002.10a
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    • pp.135-140
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    • 2002
  • Studies on the optimization of machining process can be divided into two different approaches: off-line feedrate scheduling and adaptive control. Each approach possesses its respective strong and weak points compared to each other. That is, each system can be complementary to the other. In this regard, a combined system, which is a feedrate control system for cutting force optimization, was proposed in this paper to make the best of each approach. Experimental results show that the proposed system could overcome the weak points of two systems.

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Literature Review on Job Rotation

  • Yoon, Sang-Young;Jung, Myung-Chul
    • Journal of the Ergonomics Society of Korea
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    • v.32 no.5
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    • pp.459-467
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    • 2013
  • Objective: The aim of this study is to review the studies on job rotation with various points of view and to classify the studies considering the approach methods. Background: Various work interventions were carried in order to prevent the work-related musculoskeletal disorders(WMSDs) and job rotation was considered as one of the simple and effective methods. Method: Previous studies were systematically collected with the combination of keywords such as job, task, rotation, allocation, line balancing, etc. Collected studies were classified into three categories: field study, laboratory study and optimization approach study. Results: Field studies showed that most studies focused on the evaluation of the factors causing the musculoskeletal disorder. Moreover, the effect of job rotation could be hard to identify because it required a long-period close observation. Laboratory studies covered only simple aspects of tasks or movements. Optimization approach studies showed the systematic approach to establish the job rotation scheme though many limitation and assumptions were adopted. Conclusion: This study collected and classified the previous studies on job rotation and presented the different approaches across various research areas. Application: The results of this study could help the practitioner and ergonomist how to establish the job rotation scheme.