• 제목/요약/키워드: Optimization algorithm

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효율적인 재해석 기법에 의한 RC 교각의 최적설계 (Optimization of RC Piers Based on Efficient Reanalysis Technique)

  • 조효남;민대홍;신만규
    • 한국콘크리트학회:학술대회논문집
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    • 한국콘크리트학회 2000년도 가을 학술발표회논문집(I)
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    • pp.199-204
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    • 2000
  • In this study, an optimum design algorithm using efficient reanalysis is proposed for seismic design of RC Piers. The proposed algorithm for optimization of RC Piers is based on efficient reanalysis technique. Considering structural behavior of RC Piers, several other approximation techniques, such as artificial constraint deletion is introduced to increase the efficiency of optimization. The efficiency and robustness of the proposed algorithm increase the proposed reanalysis technique is demonstrated by comparing it with a conventional optimization algorithm. A few of design examples are optimized to show the applicability of the proposed algorithm.

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ACO와 PSO 기법을 이용한 이동로봇 최적화 경로 생성 알고리즘 개발 (DEVELOPMENT OF A NEW PATH PLANNING ALGORITHM FOR MOBILE ROBOTS USING THE ANT COLONY OPTIMIZATION AND PARTICLE SWARM OPTIMIZATION METHOD)

  • 이준오;고종훈;김대원
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2008년도 심포지엄 논문집 정보 및 제어부문
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    • pp.77-78
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    • 2008
  • This paper proposes a new algorithm for path planning and obstacles avoidance using the ant colony optimization algorithm and the particle swarm optimization. The proposed algorithm is a new hybrid algorithm that composes of the ant colony algorithm method and the particle swarm optimization method. At first, we produce paths of a mobile robot in the static environment. And then, we find midpoints of each path using the Maklink graph. Finally, the hybrid algorithm is adopted to get a shortest path. We prove the performance of the proposed algorithm is better than that of the path planning algorithm using the ant colony optimization only through simulation.

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Economic Power Dispatch with Valve Point Effects Using Bee Optimization Algorithm

  • Kumar, Rajesh;Sharma, Devendra;Kumar, Anupam
    • Journal of Electrical Engineering and Technology
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    • 제4권1호
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    • pp.19-27
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    • 2009
  • This paper presents a newly developed optimization algorithm, the Bee Optimization Algorithm (BeeOA), to solve the economic power dispatch (EPD) problem. The authors have developed a derivative free and global optimization technique based on the working of the honey bee. The economic power dispatch problem is a nonlinear constrained optimization problem. Classical optimization techniques fail to provide a global solution and evolutionary algorithms provide only a good enough solution. The proposed approach has been examined and tested on two test systems with different objectives. A simple power dispatch problem is tested first on 6 generators and then the algorithm is demonstrated on 13 thermal unit systems whose incremental fuel cost function takes into account the value point loading effect. The results are promising and show the effectiveness and robustness of the proposed approach over recently reported methods.

An Optimization Method Based on Hybrid Genetic Algorithm for Scramjet Forebody/Inlet Design

  • Zhou, Jianxing;Piao, Ying;Cao, Zhisong;Qi, Xingming;Zhu, Jianhong
    • 한국추진공학회:학술대회논문집
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    • 한국추진공학회 2008년 영문 학술대회
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    • pp.469-475
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    • 2008
  • The design of a scramjet inlet is a process to search global optimization results among those factors influencing the geometry of scramjet in their ranges for some requirements. An optimization algorithm of hybrid genetic algorithm based on genetic algorithm and simplex algorithm was established for this purpose. With the sample provided by a uniform method, the compressive angles which also are wedge angles of the inlet were chosen as the inlet design variables, and the drag coefficient, total pressure recovery coefficient, pressure rising ratio and the combination of these three variables are designed specifically as different optimization objects. The contrasts of these four optimization results show that the hybrid genetic algorithm developed in this paper can capably implement the optimization process effectively for the inlet design and demonstrate some good adaptability.

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Structural optimization with teaching-learning-based optimization algorithm

  • Dede, Tayfun;Ayvaz, Yusuf
    • Structural Engineering and Mechanics
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    • 제47권4호
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    • pp.495-511
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    • 2013
  • In this paper, a new efficient optimization algorithm called Teaching-Learning-Based Optimization (TLBO) is used for the least weight design of trusses with continuous design variables. The TLBO algorithm is based on the effect of the influence of a teacher on the output of learners in a class. Several truss structures are analyzed to show the efficiency of the TLBO algorithm and the results are compared with those reported in the literature. It is concluded that the TLBO algorithm presented in this study can be effectively used in the weight minimization of truss structures.

면역-유전알고리즘을 이용한 진동최적화 (Vibration Optimization Using Immune-GA Algorithm)

  • 최병근;양보석
    • 한국소음진동공학회:학술대회논문집
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    • 한국소음진동공학회 1998년도 춘계학술대회논문집; 용평리조트 타워콘도, 21-22 May 1998
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    • pp.273-279
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    • 1998
  • An immune system has powerful abilities such as memory, recognition and learning to respond to invading antigens, and is applied to many engineering algorithm recently. In this paper, the combined optimization algorithm is proposed for multi-optimization problem by introducing the capability of the immune system that controls the proliferation of clones to the genetic algorithm. The optimizing ability of the proposed optimization algorithm is identified by using two multi-peak functions which have many local optimums and optimization of the unbalance response function for rotor model.

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Lion Optimization Algorithm (LOA): A nature-inspired metaheuristic algorithm

  • Yazdani, Maziar;Jolai, Fariborz
    • Journal of Computational Design and Engineering
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    • 제3권1호
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    • pp.24-36
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    • 2016
  • During the past decade, solving complex optimization problems with metaheuristic algorithms has received considerable attention among practitioners and researchers. Hence, many metaheuristic algorithms have been developed over the last years. Many of these algorithms are inspired by various phenomena of nature. In this paper, a new population based algorithm, the Lion Optimization Algorithm (LOA), is introduced. Special lifestyle of lions and their cooperation characteristics has been the basic motivation for development of this optimization algorithm. Some benchmark problems are selected from the literature, and the solution of the proposed algorithm has been compared with those of some well-known and newest meta-heuristics for these problems. The obtained results confirm the high performance of the proposed algorithm in comparison to the other algorithms used in this paper.

A new hybrid meta-heuristic for structural design: ranked particles optimization

  • Kaveh, A.;Nasrollahi, A.
    • Structural Engineering and Mechanics
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    • 제52권2호
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    • pp.405-426
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    • 2014
  • In this paper, a new meta-heuristic algorithm named Ranked Particles Optimization (RPO), is presented. This algorithm is not inspired from natural or physical phenomena. However, it is based on numerous researches in the field of meta-heuristic optimization algorithms. In this algorithm, like other meta-heuristic algorithms, optimization process starts with by producing a population of random solutions, Particles, located in the feasible search space. In the next step, cost functions corresponding to all random particles are evaluated and some of those having minimum cost functions are stored. These particles are ranked and their weighted average is calculated and named Ranked Center. New solutions are produced by moving each particle along its previous motion, the ranked center, and the best particle found thus far. The robustness of this algorithm is verified by solving some mathematical and structural optimization problems. Simplicity of implementation and reaching to desired solution are two main characteristics of this algorithm.

이동 통신 시스템에서 기지국 위치의 최적화 (Base Station Location Optimization in Mobile Communication System)

  • 변건식;이성신;장은영;오정근
    • 한국전자파학회논문지
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    • 제14권5호
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    • pp.499-505
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    • 2003
  • 이동 무선 통신 시스템을 설계할 때 기지국의 위치는 매우 중요한 파라미터 중 하나이다. 기지국 위치를 설계할 때 여러 가지 복잡한 변수들을 잘 조합하여 코스트가 최소가 되도록 설계해야 한다. 이러한 문제를 해결하는데 필요한 알고리즘이 조합 최적화 알고리즘이며, 지금까지 조합 최적화 기술로 Random Walk, Simulated Annealing, Tabu Search, Genetic Algorithm과 같은 전역 최적화 기술이 사용되어 왔다. 본 논문은 이동 통신시스템의 기지국 위치 최적화에 위의 4가지 알고리즘들을 적용하여 각 알고리즘의 결과를 비교 분석하며 알고리즘에 의한 최적화 과정을 보여준다.

유전알고리즘을 이용한 디젤엔진의 연소최적화 기법에 대한 연구 (An Optimization Technique for Diesel Engine Combustion Using a Micro Genetic Algorithm)

  • 김동광;조남효;차순창;조순호
    • 한국자동차공학회논문집
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    • 제12권3호
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    • pp.51-58
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    • 2004
  • Optimization of engine desist and operation parameters using a genetic algorithm was demonstrated for direct injection diesel engine combustion. A micro genetic algorithm and a modified KIVA-3V code were used for the analysis and optimization of the engine combustion. At each generation of the optimization step the micro genetic algorithm generated five groups of parameter sets, and the five cases of KIVA-3V analysis were to be performed either in series or in parallel. The micro genetic algorithm code was also parallelized by using MPI programming, and a multi-CPU parallel supercomputer was used to speed up the optimization process by four times. An example case for a fixed engine speed was performed with six parameters of intake swirl ratio, compression ratio, fuel injection included angle, injector hole number, SOI, and injection duration. A simultaneous optimization technique for the whole range of engine speeds would be suggested for further studies.