• Title, Summary, Keyword: discrete optimization

Search Result 455, Processing Time 0.038 seconds

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

  • Lee Kang-Seok;Kim Jeong-Hee;Choi Chang-Sik;Lee Li-Hyung
    • Proceedings of the Computational Structural Engineering Institute Conference
    • /
    • /
    • pp.351-358
    • /
    • 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.

  • PDF

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

  • Yim, Dong-Soon
    • Journal of the Society of Korea Industrial and Systems Engineering
    • /
    • v.36 no.3
    • /
    • pp.63-70
    • /
    • 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.

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

  • Kim, Jong-Ok;Park, Chan-Gi;Cha, Sang-Sun
    • Journal of The Korean Society of Agricultural Engineers
    • /
    • v.52 no.6
    • /
    • pp.49-56
    • /
    • 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
    • /
    • v.3 no.4
    • /
    • pp.359-372
    • /
    • 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.

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

  • Kim, Tae-Uk
    • Proceedings of the KSME Conference
    • /
    • /
    • pp.734-739
    • /
    • 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..

  • PDF

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
    • /
    • v.4 no.2
    • /
    • pp.185-193
    • /
    • 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.

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

  • 이한주;김호수
    • Proceedings of the Computational Structural Engineering Institute Conference
    • /
    • /
    • pp.254-261
    • /
    • 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

  • PDF

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

  • 김봉익;권중현
    • Journal of Ocean Engineering and Technology
    • /
    • v.17 no.6
    • /
    • pp.53-57
    • /
    • 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.

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

  • 김봉익;권중현
    • Journal of Ocean Engineering and Technology
    • /
    • v.16 no.4
    • /
    • pp.25-31
    • /
    • 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.

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

  • 조효남;민대홍;박준용
    • Journal of the Computational Structural Engineering Institute of Korea
    • /
    • v.15 no.3
    • /
    • pp.453-462
    • /
    • 2002
  • Discrete-sizing or standardized steel profiles are used in steel design and construction practice. However, most of numerical optimization methods follow additional step(round-up discrete-sizing routine) to use the standardized steel section profiles, and accordingly the optimality of the resulting design nay be doubtful. Thus, in this paper, an efficient multi-level optimization algorithm is proposed to improve the shortcoming of the conventional optimization methods using the round-up discrete-sizing routine. Also, multi-level optimization technique with a decomposition method that separates both system-level and element-level is incorporated in the algorithm to enhance the performance of the proposed algorithms. The proposed algorithm is expected to achieve considerable improvement on both the efficiency of the numerical process and the accuracy of the global optimum.