• 대한기계학회논문집A
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• 제29권2호
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• pp.262-269
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• 2005

Optimization of a satellite structure under severe space launching environments is performed considering various design constraints. Simulate annealing, one of combinatorial optimization techniques, is used to optimize the satellite. The optimization results by the simulated annealing are compared to those by the method of modified feasible direction and genetic algorithm. Ten bar truss structure is optimized for feasibility study of the simulated annealing. Finally, the satellite structure is optimized by the simulated annealing algorithm under space environment. Weights of the satellite upper platform and propulsion module are minimized with consideration of several static and dynamic constraints. MSC/NASTRAN is used to find the static and dynamic responses. Simulated annealing has been programmed and integrated with the finite element analysis program for optimization. It is shown that the simulated annealing algorithm can be extended to the optimization of space structures.

• Journal of Electrical Engineering and Technology
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• 제10권4호
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• pp.1441-1452
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• 2015

This paper proposes a new Hybrid Particle Swarm Optimization (HPSO) method that integrates the Evolutionary Programming (EP) and Particle Swarm Optimization (PSO) techniques. The proposed method is applied to solve Economic Dispatch(ED) problems considering prohibited operating zones, ramp rate limits, capacity limits and power balance constraints. In the proposed HPSO method, the best features of both EP and PSO are exploited, and it is capable of finding the most optimal solution for the non-linear optimization problems. For validating the proposed method, it has been tested on the standard three, six, fifteen and twenty unit test systems. The numerical results show that the proposed HPSO method is well suitable for solving non-linear economic dispatch problems, and it outperforms the EP, PSO and other modern metaheuristic optimization methods reported in the recent literatures.

• Structural Engineering and Mechanics
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• 제52권3호
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• pp.445-468
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• 2014

In this paper a new particle swarm ray optimization algorithm is proposed for truss shape and size optimization with natural frequency constraints. These problems are believed to represent nonlinear and non-convex search spaces with several local optima and therefore are suitable for examining the capabilities of new algorithms. The proposed algorithm can be viewed as a hybridization of Particle Swarm Optimization (PSO) and the recently proposed Ray Optimization (RO) algorithms. In fact the exploration capabilities of the PSO are tried to be promoted using some concepts of the RO. Five numerical examples are examined in order to inspect the viability of the proposed algorithm. The results are compared with those of the PSO and some other existing algorithms. It is shown that the proposed algorithm obtains lighter structures in comparison to other methods most of the time. As will be discussed, the algorithm's performance can be attributed to its appropriate exploration/exploitation balance.

• 한국공작기계학회논문집
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• 제18권1호
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• pp.103-109
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• 2009

This paper presents structural design optimization of a micro milling machine for minimum weight and compliance using a genetic algorithm with dynamic penalty function. The optimization procedure consists of two design stages, which are the static and dynamic design optimization stages. The design problem, in this study, is to find out thickness of structural members which minimize the weight, the static compliance and the dynamic compliance of the micro milling machine under several constraints such as dimensional constraints, maximum compliance limit, and safety factor criterion. Optimization results showed a great reduction in the static and dynamic compliances at the spindle nose of the micro milling machine in spite of a little decrease in the machine weight.

• 한국항공우주학회지
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• 제30권2호
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• pp.122-129
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• 2002

우주 구조물인 하나콤 위성본체 플래폼의 구조최적화를 수행하였다. 하나콤 위성 플래폼의 최적설계에는 다양한 우주 환경 하에서 고려하기 어려운 제한 조건들이 고려된다. 이러한 제한 조건들을 고려하기 위해서 최적화 기법인 변형 유용 방향 탐색법과 유전자 알고리즘을 유한 유소 해석 기법을 사용하는 MSC/NASTRAN과 병행하여 최적화를 수행하였다. 하나콤 위성 플래폼의 최적화는 정적해석과 동해석을 통하여 베어링 응력과 고유 진동수에 대한 제한조건을 사용하여 수행하였다. 본 연구의 수행 결과 국부 최적화 기법인 변형 유용 방향 탐색법이 전역 최적화 기법인 유전자 알고리즘에 의한 최적화 보다 좋은 결과를 얻을 수 있었다. 또한, 두 기법의 최적화 모두 응력 보다는 고유 진동수에 의한 제한 조건이 최적화에 더 큰 영향을 준다는 사실을 알게 되었다. 하나콤 위성 플래폼의 최적화를 통해서 주어진 환경에 더 적합하고 안정성 있는 플래폼의 구조최적설계를 할 수 있었다.

• Journal of Mechanical Science and Technology
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• 제20권4호
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• pp.494-504
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• 2006

This research proposes a reliability-based topology optimization (RBTO) using the finite element method. RBTO is a topology optimization based on probabilistic (or reliability) constraints. Young's modulus, thickness, and loading are considered as the uncertain variables and RBTO is applied to static and eigenvalue problems. The RBTO problems are formulated and a sensitivity analysis is performed. In order to compute probability constraints, two methods-RIA and PMA-are used. Several examples show the effectiveness of the proposed method by comparing the classical safety factor method.

• 한국CDE학회논문집
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• 제16권6호
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• pp.397-406
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• 2011

Since tolerance allocation in a mobile phone camera manufacturing process greatly affects production cost and reliability of optical performance, a systematic design methodology for allocating optimal tolerances is required. In this study, we proposed the tolerance optimization procedure for determining tolerances that minimize production cost while satisfying the reliability constraints on important optical performance indices. We employed Latin hypercube sampling for evaluating the reliabilities of optical performance and a function-based sequential approximate optimization technique that can reduce computational burden and well handle numerical noise in the tolerance optimization process. Using the suggested tolerance optimization approach, the optimal production cost was decreased by 30.3 % compared to the initial cost while satisfying the two constraints on the reliabilities of optical performance.

• 한국생산제조학회지
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• 제22권1호
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• pp.63-69
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• 2013

In order to find the optimum design of structures that have characteristic natural frequency range, a numerical optimization method to solving eigenvalue problems is a widely used approach. However in the most cases, it is difficult to decide the accurate thickness and shape of structures that have allowable natural frequency in design constraints. Parallel analysis algorithm involving the feasible direction optimization method and Rayleigh-Ritz eigenvalue solving method is developed. The method is implemented by using finite element method. It calculates the optimal thickness and the thickness ratio of individual elements of the 2-D plane element through a parallel algorithm method which satisfy the design constraint of natural frequency. As a result this method of optimization for natural frequency by using finite element method can determine the optimal size or its ratio of geometrically complicated shape and large scale structure.

• Industrial Engineering and Management Systems
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• 제13권4호
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• pp.442-448
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• 2014

Portfolio optimization in the presence of estimation error can be stabilized by incorporating norm-constraints; this result was shown by DeMiguel et al. (A generalized approach to portfolio optimization: improving performance by constraining portfolio norms, Management Science, 5, 798-812, 2009), who reported empirical performance better than numerous competing approaches. We extend the idea of norm-constraints by introducing a powerful enhancement, grouped selection for portfolio optimization. Here, instead of merely penalizing norms of the assets being selected, we penalize groups, where within a group assets are treated alike, but across groups, the penalization may differ. The idea of groupwise selection is grounded in statistics, but to our knowledge, it is novel in the context of portfolio optimization. Novelty aside, the real benefits of groupwise selection are substantiated by experiments; our results show that groupwise asset selection leads to strategies with lower variance, higher Sharpe ratios, and even higher expected returns than the ordinary norm-constrained formulations.

• Structural Engineering and Mechanics
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• 제43권6호
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• pp.795-821
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• 2012

The size and topology of geometrically nonlinear dome structures are optimized thereby minimizing both its entire weight & joint (node) displacements and maximizing load-carrying capacity. Design constraints are implemented from provisions of American Petroleum Institute specification (API RP2A-LRFD). In accordance with the proposed design constraints, the member responses computed by use of arc-length technique as a nonlinear structural analysis method are checked at each load increment. Thus, a penalization process utilized for inclusion of unfeasible designations to genetic search is correspondingly neglected. In order to solve this complex design optimization problem with multiple objective functions, Non-dominated Sorting Genetic Algorithm II (NSGA II) approach is employed as a multi-objective optimization tool. Furthermore, the flexibility of proposed optimization is enhanced thereby integrating an automatic dome generating tool. Thus, it is possible to generate three distinct sphere-shaped dome configurations with varying topologies. It is demonstrated that the inclusion of brace (diagonal) members into the geometrical configuration of dome structure provides a weight-saving dome designation with higher load-carrying capacity. The proposed optimization approach is recommended for the design optimization of geometrically nonlinear dome structures.