• Interaction and multiscale mechanics
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• 제6권2호
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• pp.137-156
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• 2013

In this paper, a meshfree shell adaptive procedure is developed for the applications in the sheet metal forming simulation. The meshfree shell formulation is based on the first-order shear deformable shell theory and utilizes the degenerated continuum and updated Lagrangian approach for the nonlinear analysis. For the sheet metal forming simulation, an h-type adaptivity based on the meshfree background cells is considered and a geometric error indicator is adopted. The enriched nodes in adaptivity are added to the centroids of the adaptive cells and their shape functions are computed using a first-order generalized meshfree (GMF) convex approximation. The GMF convex approximation provides a smooth and non-negative shape function that vanishes at the boundary, thus the enriched nodes have no influence outside the adapted cells and only the shape functions within the adaptive cells need to be re-computed. Based on this concept, a multi-level refinement procedure is developed which does not require the constraint equations to enforce the compatibility. With this approach the adaptive solution maintains the order of meshfree approximation with least computational cost. Two numerical examples are presented to demonstrate the performance of the proposed method in the adaptive shell analysis.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.1876-1879
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• 1997

This paper developes an efficient algorithm for the minimum distance calculation between general polyhedra(convex and/or concave). The polyhedron approximates and object using flat polygons which composed of more than three veritices. The algorithm developed in this paper basically computes minimun distance betwen two convex polygons and finds a set of polygons whcih makes a global minimum distance. The advantage of the algorithm is that the global minimum distance can be computed in any cases. But the big disadvantage is that minimum distance computing time is repidly increased with the number of polygons which used to approximate an object. This paper developes a method to eliminate unnecessary sets of polygons, and an efficinet algorithm to compute a minimum distance between two polygons in order to compensate the inherent disadvantage of the algorithm. It takes only a few times iteration to find minimum distance for msot polygons. The correctness of the algortihm are visually tested with a line which connects two points making a global minimum distance of simple convex object(box) and concave object(pipe). The algorithm can find minimum distance between two convex objects made of about 200 polygons respectively less than a second computing time.

• 한국게임학회 논문지
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• 제10권1호
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• pp.157-165
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• 2010

본 논문에서는 컨벡스 헐을 이용한 구 좌표계 기반 실시간 렌더링 알고리즘이 제안되었다. OpenGL 렌더링 파이프라인은 물체의 모든 정점들을 고려하지만, 제안된 방법은 물체의 가시 삼각형들을 검사하여 보이는 정점들만을 고려한다. 본 논문에서는 구좌표계 표현에서의 물체의 가시 영역을 결정하기 위하여, 카메라 절두체를 이루는 6개의 평면 방정식과 물체의 경계구와의 기하 관계를 이용한다. 또한 대상 물체의 컨벡스 헐(convex hull)의 최대 측면 성분(maximum side factor)을 고려하여 은면(hidden surface)을 제거하는 효과적인 방법이 구현되었다. 실험결과로부터 결과 영상이 원본 영상과 거의 같고, 렌더링 성능이 크게 개선됐음을 확인하였다.

• Kyungpook Mathematical Journal
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• 제56권2호
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• pp.583-595
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• 2016

Archimedes showed that for a point P on a parabola X and a chord AB of X parallel to the tangent of X at P, the area S of the region bounded by the parabola X and chord AB is four thirds of the area T of triangle ${\Delta}ABP$. It is well known that the area U formed by three tangents to a parabola is half of the area T of the triangle formed by joining their points of contact. Recently, the first and third authors of the present paper and others proved that among strictly locally convex curves in the plane ${\mathbb{R}}^2$, these two properties are characteristic ones of parabolas. In this article, in order to generalize the above mentioned property $S={\frac{4}{3}}T$ for parabolas we study strictly locally convex curves in the plane ${\mathbb{R}}^2$ satisfying $S={\lambda}T+{\nu}U$, where ${\lambda}$ and ${\nu}$ are some functions on the curves. As a result, we present two conditions which are necessary and sufficient for a strictly locally convex curve in the plane to be an open arc of a parabola.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권5호
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• pp.1503-1515
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• 2023

This paper considers the jointly active and passive beamforming design in the IRS-aided MISO downlink vehicle communication system where both V2I and V2V communication paradigms coexist. We formulate the problem as an optimization problem aiming to minimize the total transmit power of the base station subject to SINR requirements of both V2I and V2V users, total transmit power of base station and IRS's phase shift constraints. To deal with this non-convex problem, we propose a method which can alternately optimize the active beamforming at the base station and the passive beamforming at the IRS. By using first-order Taylor expansion, matrix analysis theory and penalized convex-concave process method, the non-convex optimization problem with coupled variables is converted into two decoupled convex sub-problems. The simulation results show that the proposed alternate optimization algorithm can significantly decrease the total transmit power of the vehicle base station.

• 한국해양공학회지
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• 제18권2호
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• pp.77-82
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• 2004

The purpose of this study is to develop a nesting algorithm, using a genetic algorithm to optimize nesting order, and modified No Fit Polygon(NFP) methodology to place parts with the order generated from the previous genetic algorithm. Various genetic algorithm techniques, which have thus far been applied to the Travelling Salesman Problem, were tested. The partially mapped crossover method, the inversion method for mutation, the elitist strategy, and the linear scaling method of fitness value were selected to optimize the nesting order. A modified NFP methodology, with improved searching capability for non-convex polygon, was applied repeatedly to the placement of parts according to the order generated from previous genetic algorithm. Modified NFP, combined with the genetic algorithms that have been proven in TSP, were applied to the nesting problem. For two example cases, the combined nesting algorithm, proposed in this study, shows better results than that from previous studies.

• 제어로봇시스템학회논문지
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• 제11권4호
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• pp.279-283
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• 2005

This paper deals with the design of a low-order H/sub ∞/ controller by using an iterative linear matrix inequality (LMI) method. The low-order H/sub ∞/ controller is represented in terms of LMIs with a rank condition. To solve the non-convex rank-constrained LMI problem, the recently developed penalty function method is applied. With an increasing sequence of the penalty parameter, the solution of the penalized optimization problem moves towards the feasible region of the original non-convex problem. Numerical experiments showed the effectiveness of the proposed algorithm.

• 한국정보통신학회논문지
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• 제27권1호
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• pp.109-116
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• 2023

본 논문에서는 다중 리더 에이전트와 추종 에이전트들로 구성된 2차 다중 에이전트 시스템의 봉쇄제어 문제를 연구하였다. 봉쇄제어의 목표는 추종 에이전트들을 다중 리더 에이전트들에 의해 생성되는 convex hulll을 추종하도록 하는 데에 있다. 따라서 리더 에이전트들에 의해 전체 그룹을 제어함으로써 다중 에이전트 시스템의 군집 행동을 얻을 수 있다. 본 논문에서 리더 에이전트들은 일정한 속도로 움직이고 추종 개체들은 입력 포화가 존재하는 경우를 고려하였다. 또한 추종 에이전트들은 이웃한 에이전트들과 상태 정보를 교환할 수 있고, 이웃과의 상대 상태 정보만 이용 가능하다 가정하였다. 이러한 가정하에 움직이는 리더 에이전트들을 고려한 봉쇄제어 문제를 해결하기 위해 비례-적분 기반의 분산제어 알고리즘을 제안하였다. 또한, 라살레 불변의 법칙을 기반으로 추종 에이전트들의 리더 에이전트들에 의해 생성되는 convex hull로 수렴을 보장하는 제어 이득들에 대한 조건들을 조사하였고 시스템 파라미터의 정보만으로 설계할 수 있음을 보였다. 마지막으로 모의실험을 통한 이론적 결과를 검증하였다.

• 한국경영과학회지
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• 제32권2호
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• pp.99-107
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• 2007

We consider (worst-case) robust optimization versions of the Economic Order Quantity (EOQ) model with decreasing cost functions. Two variants of the EOQ model are discussed, in which the purchasing costs are decreasing power functions in either the order quantity or demand rate. We develop the corresponding worst-case robust optimization models of the two variants, where the parameters in the purchasing cost function of each model are uncertain but known to lie in an ellipsoid. For the robust EOQ model with the purchasing cost being a decreasing function of the demand rate, we derive the analytical optimal solution. For the robust EOQ model with the purchasing cost being a decreasing function of the order quantity, we prove that it is a convex optimization problem, and thus lends itself to efficient numerical algorithms.

• Management Science and Financial Engineering
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• 제18권2호
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• pp.23-27
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• 2012

The problem of jointly determining a robust optimal bundle of price and order quantity for a retailer in a single-retailer, single supplier, single-product supply chain is considered. Demand is modeled as a decreasing power function of product price, and unit purchasing cost is modeled as a decreasing power function of order quantity and demand. Parameters defining the two power functions are uncertain but their possible values are characterized by ellipsoids. We extend a previous study in two ways; the purchasing cost function is generalized to take into account the economies of scale realized by higher product demand in addition to larger order quantity, and an exact transformation into an equivalent convex optimization program is developed instead of a geometric programming approximation scheme proposed in the previous study.