• Title/Summary/Keyword: 파레토 최적해

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Multi-Objective Optimization for Orthotrpic Steel Deck Bridges (강상판교의 다목적 최적설계)

  • Cho, Hyo Nam;Chung, Jee Seung;Min, Dae Hong
    • Journal of Korean Society of Steel Construction
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    • v.14 no.3
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    • pp.395-402
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    • 2002
  • This study proposed a muti-objective optimum design method for rational optimizing of orthotropic steel deck bridges. This multi-objective optimum design method was found to be effective in optimizing multi-objective problems, considering cost and deflection functions. It may ve difficult to optimize orthotropic steel deck bridges using a conventional optimization, since the bridges have several parts and show complex structural behaviors. Therefore, the Pareto curve can be obtained by performing the multi-objective optimization for real orthotropic steel deck bridges, using the multi-level technique with excellent efficiency. A reasonable and economical design can be attained using the Parato curve in the cost and deflection functions of the bridge. Thus, more reasonable design values can be determined based on a comparison with those using a conventional design procedure.

A Two-tier Optimization Approach for Decision Making in Many-objective Problems (고도 다목적 문제에서의 의사 결정을 위한 이중 최적화 접근법)

  • Lee, Ki-Baek
    • The Journal of the Korea Contents Association
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    • v.15 no.7
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    • pp.21-29
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    • 2015
  • This paper proposes a novel two-tier optimization approach for decision making in many-objective problems. Because the Pareto-optimal solution ratio increases exponentially with an increasing number of objectives, simply finding the Pareto-optimal solutions is not sufficient for decision making in many-objective problems. In other words, it is necessary to discriminate the more preferable solutions from the other solutions. In the proposed approach, user preference-oriented as well as diverse Pareto-optimal solutions can be obtained as candidate solutions by introducing an additional tier of optimization. The second tier of optimization employs the corresponding secondary objectives, global evaluation and crowding distance, which were proposed in previous works, to represent the users preference to a solution and the crowdedness around a solution, respectively. To demonstrate the effectiveness of the proposed approach, decision making for some benchmark functions is conducted, and the outcomes with and without the proposed approach are compared. The experimental results demonstrate that the decisions are successfully made with consideration of the users preference through the proposed approach.

Coordinated Multiple Reservoir Operation Using a DEA-based Ranking Procedure (DEA기반 순위결정 절차를 활용한 저수지군 연계운영)

  • Jeon, Seung-Mok;Kim, Sheung-Kown
    • Proceedings of the Korea Water Resources Association Conference
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    • 2007.05a
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    • pp.2089-2093
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    • 2007
  • 저수지군 연계운영 문제는 서로 상충되는 목적들이 존재하고, 다양한 평가 기준들이 존재하는 다목적 특성을 갖는 문제이다. 때문에 저수지군 연계운영 문제에 다중목적계획법이 많이 사용되고 있으나 문제의 해결을 위해 사용한 다수의 목적간의 가중치 설정에 의사결정자의 주관적요소가 반영 될 수도 있고, 설정된 가중치에 따라 결과 값이 민감하게 반응하여 의사결정자가 바람직한 가중치 설정에 어려움이 있다. 본 연구의 목적은 다중 목적 특성이 존재하는 저수지군 연계운영 문제에 다요소 의사결정기법 적용하여 바람직한 저수지별 저수 가중치를 선정하는 방법을 제안하는 것이다. 제안하는 저수 가중치 선정 절차는, 우선 GA-CoMOM (Genetic-Algorithm Coordinate Multi-reservoir Operation Model)을 통해 수계 전체 관점에서 저수량과 발전량의 상충되는 목적에 대한 파레토 최적해와 각 최적해에 해당하는 저수지별 저수 가중치를 도출한다. 다음 단계로 다요소 의사결정기법중에 하나인 수정된 거리척도 기반의 DEA 순위 선정 절차를 이용하여 도출된 최적해들의 운영 결과를 평가하여 파레토 최적해군 중에 선호해를 결정하고, 결정된 선호해의 저수지별 저수 가중치를 해당 기간의 저수 가중치로 선정한다. 설명한 선호 가중치 선정 절차를 금강 수계에 적용해 보고 저수지 연계운영에서 바람직한 가중치를 도출할 수 있음을 보인다.

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Development of Pareto Artificial Life Optimization Algorithm (파레토 인공생명 최적화 알고리듬의 제안)

  • Song, Jin-Dae;Yang, Bo-Suk
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.30 no.11 s.254
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    • pp.1358-1368
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    • 2006
  • This paper proposes a Pareto artificial life algorithm for solving multi-objective optimization problems. The artificial life algorithm for optimization problem with a single objective function is improved to handle Pareto optimization problem through incorporating the new method to estimate the fitness value for a solution and the Pareto list to memorize and to improve the Pareto optimal set. The proposed algorithm was applied to the optimum design of a journal bearing which has two objective functions. The Pareto front and the optimal solution set for the application were presented to give the possible solutions to a decision maker or a designer. Furthermore, the relation between linearly combined single-objective optimization problem and Pareto optimization problem has been studied.

Parameter estimation of unsteady flow model using mulit-objective optimization and minimax regret approach (다목적최적화와 최소최대 후회도 방법에 의한 부정류 계산모형의 매개변수 추정)

  • Li, Li;Chung, Eun-Sung;Jun, Kyung Soo
    • Proceedings of the Korea Water Resources Association Conference
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    • 2017.05a
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    • pp.310-310
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    • 2017
  • 홍수추적 모형의 적절성을 결정하는 중요한 요소 중 하나는 모형의 매개변수이다. 특히 자연하천에 관한 부정류 계산모형의 매개변수인 조도계수는 하상재료의 특성에 따라 좌우되는 표피마찰뿐만 아니라 하상의 굴곡 등 단면형의 변화에 따른 형상손실 및 하천의 사행에 따른 손실 효과 등을 포괄적으로 내포하고 있기 때문에 모든 하천구간에 대하여 일반적으로 적용할 수 있는 조도계수의 값을 하나로 결정하기는 어렵다. 또한 조도계수는 흐름조건, 즉 유량 또는 수위의 변화에 따른 가변성을 갖고 있기 때문에, 흐름이 시간 및 공간적으로 변화하는 부정류 계산모형에 있어서는 더욱 그러하다. 그러므로 본 연구에서는 조도계수의 가변성과 다수 지점의 관측치를 고려한 모형보정의 결과로부터 얻은 파레토 최적화와 최소최대 후회도 방법(Minimax regret approach, MRA)을 결합하여 부정류 계산모형의 안정적인 매개변수를 선정할 수 있는 방법을 제안하였다. 여러 지점의 관측치를 고려한 모형의 보정은 다목적 최적화 문제로서, 여러 지점에 대한 가중치를 결합하여 얻은 하나의 목적함수에 대하여 여러 번의 개별 최적화를 수행함으로써 다수의 파레토 최적해들을 구할 수 있는 통합접근법을 적용하였다. 이때 유량에 따른 조도계수의 가변성을 나타내는 두 개의 매개변수로 구성된 관계식을 이용하여 두 구간에 대한 매개변수들을 모형의 추정 대상 매개변수로서 최적화하였다. 이 후 각기 다른 홍수사상에 대해 보정과 검증을 수행하였으며 각각에 대한 평가지표의 후회도를 정량화하였고 최종 안정적인 매개변수를 추정하기 위해 MRA를 이용하여 종합적인 순위를 도출하였다. MRA는 완전히 불확실한 의사결정 상황에서 유용한 방법으로 알려져 있는데 가장 나쁜 순위가 가장 좋은 것을 선택할 수 있게 하는 보수적인 의사결정기법이다. 계산결과 추정된 모형의 가변조도계수와 그로부터 얻은 두 개 지점에서의 평가지표인 RMSE는 두 지점에 대한 가중치의 조합에 따라 선택되는 매개변수 값에 따라 달라짐을 알 수 있었다. 본 연구에서 제시한 방법은 수문 및 수리모형의 다수의 관측지점의 자료를 이용한 매개변수 산정문제에 있어서 안정적인 해를 도출할 수 있다.

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Multi-objective Optimization of an Injection Mold Cooling Circuit for Uniform Cooling (사출금형의 균일 냉각을 위한 냉각회로의 다중목적함수 최적설계)

  • Park, Chang-Hyun;Park, Jung-Min;Choi, Jae-Hyuk;Rhee, Byung-Ohk;Choi, Dong-Hoon
    • Transactions of the Korean Society of Automotive Engineers
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    • v.20 no.1
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    • pp.124-130
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    • 2012
  • An injection mold cooling circuit for an automotive front bumper was optimally designed in order to simultaneously minimize the average of the standard deviations of the temperature and the difference in mean temperatures of the upper and lower molds for uniform cooling. The temperature distribution for a specified design was evaluated by Moldflow Insight 2010, a commercial injection molding analysis tool. For efficient design, PIAnO (Process Integration, Automation and Optimization), a commercial PIDO tool, was used to integrate and automate injection molding analysis procedure. The weighted-sum method was used to handle the multi-objective optimization problem and PQRSM, a function-based sequential approximate optimizer equipped in PIAnO, to handle numerically noisy responses with respect to the variation of design variables. The optimal average of the standard deviations and difference in mean temperatures were found to be reduced by 9.2% and 56.52%, respectively, compared to the initial ones.

A Simulation-based Optimization Approach for the Selection of Design Factors (설계 변수 선택을 위한 시뮬레이션 기반 최적화)

  • Um, In-Sup;Cheon, Hyeon-Jae;Lee, Hong-Chul
    • Journal of the Korea Society for Simulation
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    • v.16 no.2
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    • pp.45-54
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    • 2007
  • In this article, we propose a different modeling approach, which aims at the simulation optimization so as to meet the design specification. Generally, Multi objective optimization problem is formulated by dependent factors as objective functions and independent factors as constraints. However, this paper presents the critical(dependent) factors as objective function and design(independent) factors as constraints for the selection of design factors directly. The objective function is normalized far the generalization of design factors while the constraints are composed of the simulation-based regression metamodels fer the critical factors and design factor's domain. Then the effective and fast solution procedure based on the pareto optimal solution set is proposed. This paper provides a comprehensive framework for the system design using the simulation and metamodels. Therefore, the method developed for this research can be adopted for other enhancements in different but comparable situations.

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Evaluation on the Reliability Attributes of Finite Failure NHPP Software Reliability Model Based on Pareto and Erlang Lifetime Distribution (파레토 및 어랑 수명분포에 근거한 유한고장 NHPP 소프트웨어 신뢰성모형의 신뢰도 속성에 관한 평가)

  • Min, Kyung-il
    • Journal of Industrial Convergence
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    • v.18 no.3
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    • pp.19-25
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    • 2020
  • In the software development process, software reliability evaluation is a very important issue. In particular, finding the optimal development model that satisfies high reliability is the more important task for software developers. For this, in this study, Pareto and Erlang life distributions were applied to the finite failure NHPP model to evaluate the reliability attributes. For this purpose, parametric estimation is applied to the maximum likelihood estimation method, and nonlinear equations are calculated using the bisection method. As a result, the Erlang model showed better performance than the Pareto model in the evaluation of the strength function and the mean value function. Also, as a result of inputting future mission time and evaluating reliability, the Erlang model showed an effectively high trend together with the Pareto model, while the Goel-Okumoto basic model showed a decreasing trend. In conclusion, the Erlang model is the best model among the proposed models. Through this study, it is expected that software developers will be able to use it as a basic guideline for exploring and evaluating the optimal software reliability model.

Goal-Pareto based NSGA Optimization Algorithm (Goal-Pareto 기반의 NSGA 최적화 알고리즘)

  • Park, Jun-Su;Park, Soon-Kyu;Shin, Yo-An;Yoo, Myung-Sik;Lee, Won-Cheol
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.44 no.2 s.314
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    • pp.108-115
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    • 2007
  • This paper proposes a new optimization algorithm prescribed by GBNSGA(Goal-Pareto Based Non-dominated Sorting Genetic Algorithm) whose result satisfies the user's needs and goals to enhance the performance of optimization. Typically, lots of real-world engineering problems encounter simultaneous optimization subject to satisfying prescribed multiple objectives. Unfortunately, since these objectives might be mutually competitive, it is hardly to find a unique solution satisfying every objectives. Instead, many researches have been investigated in order to obtain an optimal solution with sacrificing more than one objectives. This paper introduces a novel optimization scheme named by GBNSGA obeying both goals as well as objectives as possible as it can via allocating candidated solutions on Pareto front, which enhances the performance of Pareto based optimization. The performance of the proposed GBNSGA will be compared with that of the conventional NSGA and weighted-sum approach.