• 제목, 요약, 키워드: discrete optimization

검색결과 455건 처리시간 0.029초

Harmony Search Algorithm-Based Approach For Discrete Size Optimization of Truss Structures

  • Lee Kang-Seok;Kim Jeong-Hee;Choi Chang-Sik;Lee Li-Hyung
    • 한국전산구조공학회:학술대회논문집
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    • pp.351-358
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    • 2005
  • Many methods have been developed and are in use for structural size optimization problems, In which the cross-sectional areas or sizing variables are usually assumed to be continuous. In most practical structural engineering design problems, however, the design variables are discrete. This paper proposes an efficient optimization method for structures with discrete-sized variables based on the harmony search (HS) meta-heuristic algorithm. The recently developed HS algorithm was conceptualized using the musical process of searching for a perfect state of harmony. It uses a stochastic random search instead of a gradient search so that derivative information is unnecessary In this paper, a discrete search strategy using the HS algorithm is presented in detail and its effectiveness and robustness, as compared to current discrete optimization methods, are demonstrated through a standard truss example. The numerical results reveal that the proposed method is a powerful search and design optimization tool for structures with discrete-sized members, and may yield better solutions than those obtained using current method.

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다수의 값을 갖는 이산적 문제에 적용되는 Particle Swarm Optimization (Particle Swarm Optimizations to Solve Multi-Valued Discrete Problems)

  • 임동순
    • 산업경영시스템학회지
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    • v.36 no.3
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    • pp.63-70
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    • 2013
  • Many real world optimization problems are discrete and multi-valued. Meta heuristics including Genetic Algorithm and Particle Swarm Optimization have been effectively used to solve these multi-valued optimization problems. However, extensive comparative study on the performance of these algorithms is still required. In this study, performance of these algorithms is evaluated with multi-modal and multi-dimensional test functions. From the experimental results, it is shown that Discrete Particle Swarm Optimization (DPSO) provides better and more reliable solutions among the considered algorithms. Also, additional experiments shows that solution quality of DPSO is not lowered significantly when bit size representing a solution increases. It means that bit representation of multi-valued discrete numbers provides reliable solutions instead of becoming barrier to performance of DPSO.

연속형 및 혼합이산형 최적설계법에 의한 농업용 수로교 교각 및 교대의 최적설계 (Optimum Design of Reinforced Concrete Agricultural Aqueduct Abutment and Pier Using Continuous and Mixed-Discrete Optimization Methods)

  • 김종옥;박찬기;차상선
    • 한국농공학회논문집
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    • v.52 no.6
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    • pp.49-56
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    • 2010
  • This study was conducted to find out the best optimum design method for the design of reinforced concrete agricultural aqueduct abutment and pier structures. The mixed-discrete optimization and continuous optimization method were applied to the design of reinforced concrete agricultural aqueduct abutment and pier and the results of these optimization methods were compared each other. It is proved that mixed-discrete optimization method is more reliable, efficient and reasonable than continuous optimization method for the optimum design of the reinforced concrete agricultural aqueduct abutment and pier.

Approximate discrete variable optimization of plate structures using dual methods

  • Salajegheh, Eysa
    • Structural Engineering and Mechanics
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    • v.3 no.4
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    • pp.359-372
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    • 1995
  • This study presents an efficient method for optimum design of plate and shell structures, when the design variables are continuous or discrete. Both sizing and shape design variables are considered. First the structural responses such as element forces are approximated in terms of some intermediate variables. By substituting these approximate relations into the original design problem, an explicit nonlinear approximate design task with high quality approximation is achieved. This problem with continuous variables, can be solved by means of numerical optimization techniques very efficiently, the results of which are then used for discrete variable optimization. Now, the approximate problem is converted into a sequence of second level approximation problems of separable form and each of which is solved by a dual strategy with discrete design variables. The approach is efficient in terms of the number of required structural analyses, as well as the overall computational cost of optimization. Examples are offered and compared with other methods to demonstrate the features of the proposed method.

이산 섬유 배열각을 이용한 복합재료 적층 평판의 최적 설계 (Layup Optimization for Composite Laminates with Discrete Ply Angles)

  • 김태욱
    • 대한기계학회:학술대회논문집
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    • pp.734-739
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    • 2001
  • In this paper, an algorithm for stacking sequence optimization which deals with discrete ply angles is used for optimization of composite laminated plates. To handle discrete ply angles, the branch and bound method is modified. Numerical results show that the optimal stacking sequence is found with fewer evaluations of objective function than expected with the size of feasible region, which shows the algorithm can be effectively used for layup optimization of composite laminates..

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Photovoltaic System Allocation Using Discrete Particle Swarm Optimization with Multi-level Quantization

  • Song, Hwa-Chang;Diolata, Ryan;Joo, Young-Hoon
    • Journal of Electrical Engineering and Technology
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    • v.4 no.2
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    • pp.185-193
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    • 2009
  • This paper presents a methodology for photovoltaic (PV) system allocation in distribution systems using a discrete particle swarm optimization (DPSO). The PV allocation problem is in the category of mixed integer nonlinear programming and its formulation may include multi-valued dis-crete variables. Thus, the PSO requires a scheme to deal with multi-valued discrete variables. This paper introduces a novel multi-level quantization scheme using a sigmoid function for discrete particle swarm optimization. The technique is employed to a standard PSO architecture; the same velocity update equation as in continuous versions of PSO is used but the particle's positions are updated in an alternative manner. The set of multi-level quantization is defined as integer multiples of powers-of-two terms to efficiently approximate the sigmoid function in transforming a particle's position into discrete values. A comparison with a genetic algorithm (GA) is performed to verify the quality of the solutions obtained.

다중변위 구속조건하에서 고층철골조의 이산형 최적화 (Discrete Optimization of Tall Steel Frameworks under Multiple Drift Constraints)

  • 이한주;김호수
    • 한국전산구조공학회:학술대회논문집
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    • pp.254-261
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    • 1998
  • This study presents a discrete optimization of tall steel buildings under multiple drift constraints using a dual method. Dual method can replace the primary optimization problem with a sequence of approximate explicit subproblems. Since each subproblem is convex and separable, it can be efficiently solved by using a dual formulation. Specifically, this study considers the discrete-optimization problem due to the commercial standard steel sections to select member sizes. The results by the proposed method will be compared with those of the conventional optimality criteria method

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유전자 알고리즘을 이용한 트러스의 최적설계 (Optimum Design of Trusses Using Genetic Algorithms)

  • 김봉익;권중현
    • 한국해양공학회지
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    • v.17 no.6
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    • pp.53-57
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    • 2003
  • Optimum design of most structural system requires that design variables are regarded as discrete quantities. This paper presents the use of Genetic Algorithm for determining the optimum design for truss with discrete variables. Genetic Algorithm are know as heuristic search algorithms, and are effective global search methods for discrete optimization. In this paper, Elitism and the method of conferring penalty parameters in the design variables, in order to achieve improved fitness in the reproduction process, is used in the Genetic Algorithm. A 10-Bar plane truss and a 25-Bar space truss are used for discrete optimization. These structures are designed for stress and displacement constraints, but buckling is not considered. In particular, we obtain continuous solution using Genetic Algorithms for a 10-bar truss, compared with other results. The effectiveness of Genetic Algorithms for global optimization is demonstrated through two truss examples.

유전자 알고리즘을 이용한 뼈대구조물의 이산최적화 (Discrete Optimization of Plane Frame Structures Using Genetic Algorithms)

  • 김봉익;권중현
    • 한국해양공학회지
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    • v.16 no.4
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    • pp.25-31
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    • 2002
  • This paper is to find optimum design of plane framed structures with discrete variables. Global search algorithms for this problem are Genetic Algorithms(GAs), Simulated Annealing(SA) and Shuffled Complex Evolution(SCE), and hybrid methods (GAs-SA, GAs-SCE). GAs and SA are heuristic search algorithms and effective tools which is finding global solution for discrete optimization. In particular, GAs is known as the search method to find global optimum or near global optimum. In this paper, reinforced concrete plane frames with rectangular section and steel plane frames with W-sections are used for the design of discrete optimization. These structures are designed for stress constraints. The robust and effectiveness of Genetic Algorithms are demonstrated through several examples.

이산형 변수를 이용한 뼈대구조물의 다단계 최적설계 (Multi-Level Optimization for Steel Frames using Discrete Variables)

  • 조효남;민대홍;박준용
    • 한국전산구조공학회논문집
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    • v.15 no.3
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    • pp.453-462
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    • 2002
  • 건설공사의 설계와 시공에서 표준화된 이산형 강재단면을 이용하고 있으나, 대부분의 최적화기법에서는 표준강재단면을 사용하기 위해 별도의 이산화 과정을 가지게 되므로 설계결과의 최적성을 보장할 수 없다. 따라서, 본 논문에서는 제안된 알고리즘의 효율성을 높이기 위해 전체구조계와 구조요소계로 나누는 다단계 알고리즘을 적용하였다 수치해석 과정의 효율성과 최적해의 정확성을 예제를 통하여 비교·검토하였다.