• Title/Summary/Keyword: global optimization

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Optimization of structural elements of transport vehicles in order to reduce weight and fuel consumption

  • Kovacs, Gyorgy
    • Structural Engineering and Mechanics
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    • v.71 no.3
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    • pp.283-290
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    • 2019
  • In global competition manufacturing companies have to produce modern, new constructions from advanced materials in order to increase competitiveness. The aim of my research was to develop a new composite cellular plate structure, which can be primarily used for structural elements of road, rail, water and air transport vehicles (e.g. vehicle bodies, ship floors). The new structure is novel and innovative, because all materials of the components of the newly developed structure are composites (laminated Carbon Fiber Reinforced Plastic (CFRP) deck plates with pultruded Glass Fiber Reinforced Plastic (GFRP) stiffeners), furthermore combines the characteristics of sandwich and cellular plate structures. The material of the structure is much more advantageous than traditional steel materials, due mainly to its low density, resulting in weight savings, causing lower fuel consumption and less environmental damage. In the study the optimal construction of a given geometry of a structural element of a road truck trailer body was defined by single- and multi-objective optimization (minimal cost and weight). During the single-objective optimization the Flexible Tolerance Optimization method, while during the multi-objective optimization the Particle Swarm Optimization method were used. Seven design constraints were considered: maximum deflection of the structure, buckling of the composite plates, buckling of the stiffeners, stress in the composite plates, stress in the stiffeners, eigenfrequency of the structure, size constraint for design variables. It was confirmed that the developed structure can be used principally as structural elements of transport vehicles and unit load devices (containers) and can be applied also in building construction.

Soccer league optimization-based championship algorithm (SLOCA): A fast novel meta-heuristic technique for optimization problems

  • Ghasemi, Mohammad R.;Ghasri, Mehdi;Salarnia, Abdolhamid
    • Advances in Computational Design
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    • v.7 no.4
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    • pp.297-319
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    • 2022
  • Due to their natural and social revelation, also their ease and flexibility, human collective behavior and teamwork sports are inspired to introduce optimization algorithms to solve various engineering and scientific problems. Nowadays, meta-heuristic algorithms are becoming some striking methods for solving complex real-world problems. In that respect in the present study, the authors propose a novel meta-innovative algorithm based on soccer teamwork sport, suitable for optimization problems. The method may be referred to as the Soccer League Optimization-based Championship Algorithm, inspired by the Soccer league. This method consists of two main steps, including: 1. Qualifying competitions and 2. Main competitions. To evaluate the robustness of the proposed method, six different benchmark mathematical functions, and two engineering design problem was performed for optimization to assess its efficiency in achieving optimal solutions to various problems. The results show that the proposed algorithm may well explore better performance than some well-known algorithms in various aspects such as consistency through runs and a fast and steep convergence in all problems towards the global optimal fitness value.

Fuzzy Relation-Based Fuzzy Neural-Networks Using a Hybrid Identification Algorithm

  • Park, Ho-Seung;Oh, Sung-Kwun
    • International Journal of Control, Automation, and Systems
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    • v.1 no.3
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    • pp.289-300
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    • 2003
  • In this paper, we introduce an identification method in Fuzzy Relation-based Fuzzy Neural Networks (FRFNN) through a hybrid identification algorithm. The proposed FRFNN modeling implement system structure and parameter identification in the efficient form of "If...., then... " statements, and exploit the theory of system optimization and fuzzy rules. The FRFNN modeling and identification environment realizes parameter identification through a synergistic usage of genetic optimization and complex search method. The hybrid identification algorithm is carried out by combining both genetic optimization and the improved complex method in order to guarantee both global optimization and local convergence. An aggregate objective function with a weighting factor is introduced to achieve a sound balance between approximation and generalization of the model. The proposed model is experimented with using two nonlinear data. The obtained experimental results reveal that the proposed networks exhibit high accuracy and generalization capabilities in comparison to other models.er models.

Optimization of Truss Structure by Genetic Algorithms (유전자 알고리즘을 이용한 트러스 구조물의 최적설계)

  • 백운태;조백희;성활경
    • Korean Journal of Computational Design and Engineering
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    • v.1 no.3
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    • pp.234-241
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    • 1996
  • Recently, Genetic Algorithms(GAs), which consist of genetic operators named selection crossover and mutation, are widely adapted into a search procedure for structural optimization. Contrast to traditional optimal design techniques which use design sensitivity analysis results, GAs are very simple in their algorithms and there is no need of continuity of functions(or functionals) any more in GAs. So, they can be easily applicable to wide territory of design optimization problems. Also, virtue to multi-point search procedure, they have higher probability of convergence to global optimum compared with traditional techniques which take one-point search method. The introduction of basic theory on GAs, and the application examples in combination optimization of ten-member truss structure are presented in this paper.

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Optimal Design of a Transformer Core Using DEAS (DEAS를 이용한 변압기 코아의 최적설계)

  • Kim, Tae-Gyu;Kim, Jong-Wook
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.56 no.6
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    • pp.1055-1063
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    • 2007
  • This paper introduces an optimal design technique for a 250-watt isolation transformer using an optimization method, dynamic encoding algorithm for searches (DEAS). Although the optimal design technique for transformers dates back to 1970s and various optimization methods have been developed so far, literature concerning global optimization for transformer core design is rarely found against its importance. In this paper, core configuration of the isolation transformer whose performance is computed by complex mathematical steps is optimized with DEAS. The optimization result confirms that DEAS can be successfully employed to transformer core design for various performance specifications only by adjusting weight factors in cost function.

Conditional Value-at-Risk Optimization for Conversion of Convertible Bonds (전환사채 주식전환을 위한 조건부 VaR 최적화)

  • Park, Koo-Hyun;Shim, Eun-Tak
    • Korean Management Science Review
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    • v.28 no.2
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    • pp.1-16
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    • 2011
  • In this study we suggested two optimization models to answer a question from an investor standpoint : how many convertible bonds should one convert, and how many keep? One model minimizes certain risk to the minimum required expected return, the other maximizes the expected return subject to the maximum acceptable risk. In comparison with Markowitz portfolio models, which use the variance of return, our models used Conditional Value-at-Risk(CVaR) for risk measurement. As a coherent measurement, CVaR overcomes the shortcomings of Value-at-Risk(VaR). But there are still difficulties in solving CVaR including optimization models. For this reason, we adopted Rockafellar and Uryasev's[18, 19] approach. Then we could approximate the models as linear programming problems with scenarios. We also suggested to extend the models with credit risk, and applied examples of our models to Hynix 207CB, a convertible bond issued by the global semiconductor company Hynix.

A homotopy method for solving nonlinear optimization problems (비선형 최적화 문제를 풀기 위한 Homotopy 방법)

  • Han, Gyu-Sik;Lee, Dae-Won;Lee, Jae-Uk
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2004.05a
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    • pp.111-114
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    • 2004
  • 기존의 도함수에 기초한 수치적 최적화 기법들(derivative-based optimization)은 비선형 최적화 문제를 풀기 위해 목적식의 1차 도함수의 정보를 이용하여 정류점(stable point)인 최적해를 찾아 나가는 방식을 취하고 있다. 그러나 이런 방법들은 목적식의 국부 최적해(local minimum)을 찾는 것은 보장하나, 전역 최적해(global minimum)를 찾는 데에는 실패할 경우가 많다. 국부 최적해와 전역 최적해는 모두 목적식의 1차 도함수가 '0'인 값을 가지는 특징이 있으므로, 국부 또는 전역 최적해를 구하는 구하는 과정은 목적식의 1차 도함수가 '0'인 해를 찾는 방정식 문제로 변환될 수 있다. 따라서 본 논문에서는 비선형 방정식의 해를 찾는데 좋은 성능을 보이는 Homotopy 방법을 이용하여 목적식의 1차 도함수에 관한 비선형 방정식을 풀고, 이를 통해 비선형 최적화 문제의 모든 국부 최적해를 찾아냄으로써 전역 최적화 문제를 해결하는 방법을 제안하고자 한다. 제안된 방법론을 다양한 전역 최적화 문제에 적용한 결과, 기존의 방법들에 비해 더 좋은 성능을 보임을 알 수 있었다.

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Parameter optimization for SVM using dynamic encoding algorithm

  • Park, Young-Su;Lee, Young-Kow;Kim, Jong-Wook;Kim, Sang-Woo
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.2542-2547
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    • 2005
  • In this paper, we propose a support vector machine (SVM) hyper and kernel parameter optimization method which is based on minimizing radius/margin bound which is a kind of estimation of leave-one-error. This method uses dynamic encoding algorithm for search (DEAS) and gradient information for better optimization performance. DEAS is a recently proposed optimization algorithm which is based on variable length binary encoding method. This method has less computation time than genetic algorithm (GA) based and grid search based methods and better performance on finding global optimal value than gradient based methods. It is very efficient in practical applications. Hand-written letter data of MNI steel are used to evaluate the performance.

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Capacitor Placement in Radial Distribution Systems Using Chaotic Search Algorithm (방사상 배전계통의 커패시터 설치를 위한 카오스 탐색알고리즘)

  • Rhee, Sang-Bong;Kim, Kyu-Ho;You, Seok-Ku
    • Proceedings of the KIEE Conference
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    • 2002.07a
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    • pp.124-126
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    • 2002
  • The general capacitor placement problem is a combinatorial optimization problem having an objective function composed of power losses and capacitor installation costs subject to bus voltage constraints. In this paper, the method employing the chaos search algorithm is proposed to solve optimal capacitor placement problem with reducing computational effort and enhancing optimality of the solution. Chaos method in optimization problem searches the global optimal solution on the regularity of chaotic motions and easily escapes from local or near optimal solution than stochastic optimization algorithms. The chaos optimization method is tested on 9 buses and 69 buses system to illustrate the effectiveness of the proposed method.

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Evaluation of Surrogate Models for Shape Optimization of Compressor Blades

  • Samad, Abdus;Kim, Kwang-Yong
    • 유체기계공업학회:학술대회논문집
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    • 2006.08a
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    • pp.367-370
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    • 2006
  • Performances of multiple surrogate models are evaluated in a turbomachinery blade shape optimization. The basic models, i.e., Response Surface Approximation, Kriging and Radial Basis Neural Network models as well as weighted average models are tested for shape optimization. Global data based errors for each surrogates are used to calculate the weights. These weights are multiplied with the respective surrogates to get the final weighted average models. The design points are selected using three level fractional factorial D-optimal designs. The present approach can help address the multi-objective design on a rational basis with quantifiable cost-benefit analysis.

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