• Computational Structural Engineering
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• v.11 no.4
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• pp.229-237
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• 1998

본 연구는 횡변위 구속조건을 받는 고층철골구조물의 이산형 최적설계를 위해 효율적인 쌍대알고리즘을 제시하고자 한다. 양함수형태의 횡변위 구속조건을 설정하기 위해 가상일의 원리가 적용되면 고층철골조의 설계변수의 수를 줄여주기 위해 쌍대알고리즘내에 단면특성관계식이 추가된다. 이 알고리즘의 검증을 위하여 횡하중을 받는 네 가지 형태의 고층철골조 예제가 제시되며, 반복과정에서 수렴된 최종물량을 기존의 최적설계방법과 비교해 봄으로써 제시된 알고리즘의 효율성이 검토된다.

• Journal of Korean Society of Steel Construction
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• v.10 no.4 s.37
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• pp.657-666
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• 1998

This study presents an effective dual algorithm for the optimal design of steel structures with displacement constraints. The dual method can replace a primary optimization problem with a sequence of approximate explicit subproblems with a simple algebraic structure. Since being convex and separable, each subproblem can be solved efficiently by the dual method. Specifically, this study uses the principle of virtual work to obtain the displacement constraint equations with an explicit form and adds the linear regression equation expressing the relationships between the cross-section properties to the dual algorithm to reduce the number of design variables. Furthermore, this study deals with the discrete optimization problem to select members with the standard steel sections. Through numerical analyses, the proposed method will be compared with the conventional optimality criteria method.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.3
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• pp.259-266
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• 2011

We present a new dual sequential approximate optimization (SAO) algorithm called SD-TDQAO (sequential dual two-point diagonal quadratic approximate optimization). This algorithm solves engineering optimization problems with a nonlinear objective and nonlinear inequality constraints. The two-point diagonal quadratic approximation (TDQA) was originally non-convex and inseparable quadratic approximation in the primal design variable space. To use the dual method, SD-TDQAO uses diagonal quadratic explicit separable approximation; this can easily ensure convexity and separability. An important feature is that the second-derivative terms of the quadratic approximation are approximated by TDQA, which uses only information on the function and the derivative values at two consecutive iteration points. The algorithm will be illustrated using mathematical and topological test problems, and its performance will be compared with that of the MMA algorithm.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.9 no.13
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• pp.45-50
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• 1986

본 연구에서 고찰한 surrogate relaxation은 Lagrangian relaxation 방법과는 달리 제약식들을 선형조합으로 묶어 문제를 푼다. 수리계획 분계가 convexity를 만족하지 못하는 경우에는 Lagrangian의 경우와 마찬가지로 surrogate gap이 발생한다. Lagrangian 쌍대이론을 토대로 surrogate optimality condition을 알아보고 수리계획법의 특별 형태인 정수선형계획법에 적용해 보았다. 일반적으로 surrogate gap은 Lagrangian gap 보다 작기 때문에 좀더 근사하게 원 문제의 최적 목적 함수값에 접근할 수 있다. 따라서 branch and bound 알고리즘을 개발할 때 중요한 정보를 제공하는 것이다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.11A
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• pp.878-891
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• 2011

We consider the throughput-maximization problem for both the up- and downlink in a wireless network with interference channels. For this purpose, we design an iterative and distributive uplink algorithm based on Lagrangian relaxation. Using the uplink power prices and network duality, we achieve throughput-maximization in the dual downlink that has a symmetric channel and an equal power budget compared to the uplink. The network duality we prove here is a generalized version of previous research [10], [11]. Computational tests show that the performance of the up- and downlink throughput for our algorithms is close to the optimal value for the channel orthogonality factor, ${\theta}{\in}$(0.5, 1]. On the other hand, when the channels are slightly orthogonal (${\theta}{\in}$(0, 0.5]), we observe some throughput degradation in the downlink. We have extended our analysis to the real downlink that has a nonsymmetric channel and an unequal power budget compared to the uplink. It is shown that the modified duality-based approach is thoroughly applied to the real downlink. Considering the complexity of the algorithms in [6] and [18], we conclude that these results are quite encouraging in terms of both performance and practical applicability of the generalized duality theorem.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1837-1838
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• 2008

최단 경로란 유향(有向) 또는 무향(無向) 그래프에서 어떤 두 점 사이를 맺는 유향 또는 무향 경로 중 가장 짧은 것, 즉 가지의 길이 합을 최소로 하는 것을 구하는 문제. 그래프가 평면 접속인 경우에는 쌍대(雙對) 그래프의 최대 흐름을 구하는 문제와 등가이다. 본 논문에서는 최단 경로 문제를 풀기 위하여 Dijkstra의 장점은 살리고 단점을 보완하는 방향성을 가지는 Dijkstra 알고리즘을 제안하였다. 사례연구를 통하여 제안한 알고리즘은 출발점에서 도착점까지 최단 경로를 빠른 시간에 찾아가는 것을 보였다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.12 no.1
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• pp.59-70
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• 1992

Quadratic programming problems(QP) have been widely used as a direction-finding subproblem in the engineering and structural design optimization. To develop an efficient solution algorithm for the QP subproblems, theoretical aspects and numerical behavior of mathematical programming methods that can be used as QP solver are studied and compared. For the solution of both primal and dual QP, Simplex, gradient projection(GRP), and augmented Lagrange multiplier algorithms are investigated and coded. From the numerical study, it is found that the primal GRP algorithm with potential constraint strategy and the dual Simplex algorithm are more attractive and effective than the others. They have theoretical robustness as well. Moreover, primal GRP algorithm is preferable in case the number of constraints is larger than the number of design variables. Favorable features of GRP and Simplex algorithm are merged into a combined algorithm, which is useful in the structural design optimization.

• Journal of the Economic Geographical Society of Korea
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• v.11 no.4
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• pp.564-579
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• 2008

It is often challenging to evaluate local spatial association among onedimensional vectors generally representing paired-location events where two points are physically or functionally connected. This is largely because of complex process of such geographic phenomena itself and partially representational complexity. This paper addresses an alternative way to identify spatially autocorrelated paired-location events (or vectors) at a local scale. In doing so, we propose a statistical algorithm combining univariate point pattern analysis for evaluating local clustering of origin-points and similarity measure of corresponding vectors. For practical use of the suggested method, we present an empirical application using transactions data in a local housing market, particularly recorded from 2004 to 2006 in Franklin County, Ohio in the United States. As a result, several locally characterized similar transactions are identified among a set of vectors showing various local moves associated with communities defined.

• Journal of the Korean Institute of Telematics and Electronics
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• v.20 no.6
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• pp.62-68
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• 1983

We suggest a Quasi- dual graph model in consideration of dynamic module assignment and relocation to assign task optimally to two processors that have different processing abilities. An optimal module partitioning and allocation to minimize total processing cost can be achieved by applying shortest-path algorithm with time complexity 0(n2) on this graph model.

• Journal of Advanced Navigation Technology
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• v.11 no.4
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• pp.388-393
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• 2007

In designing transform coders bit allocation is one of the important issues. In this paper we propose two optimal algorithms for integer bit allocation in transform coding. Based on high-resolution formulas for bit allocation, the most and least greedy algorithms are developed to optimally adjust non-integer bit rates of coefficient quantizers to integer values. In particular, a duality property is observed between the two greedy algorithms.