• 대한수학회보
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• 제38권2호
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• pp.293-302
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• 2001

We improve the greedy algorithm which is one of the general convergence criterion for certain iterative sequence in a given space by building a constructive greedy algorithm on a normed linear space using an arithmetic average of elements. We also show the degree of approximation order is still $Ο(1\sqrt{\n}$) by a bounded linear functional defined on a bounded subset of a normed linear space which offers a good approximation method for neural networks.

• 한국경영과학회지
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• 제15권2호
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• pp.97-104
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• 1990

The problem is a variation of the weighted set-covering problem (SCP) which requires the minimum-cost cover to be self-covering. It is shown that direct extension of the well-known greedy heuristic for SCP can have an arbitrarily large error in the worst case. It remains an open question whther these exists a greedy heuristic with a finite error bound.

• 대한산업공학회지
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• 제11권2호
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• pp.155-163
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• 1985

This paper presents a heuristic algorithm for a multidepot aircraft scheduling and crew scheduling with deal-head flights. This algorithm is extended from a Greedy heuristic algorithm for a multi-depot multi-salesman traveling salesman problem. We first transform a given flight schedule into a multi-depot multi-traveling salesman problem, considering aircraft flight policies and crew management constraints. Then we solve this problem by applying a modified Greedy heuristic algorithm.

• Journal of applied mathematics & informatics
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• 제32권1_2호
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• pp.129-136
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• 2014

One of the fundamental issues in the design of dynamic spectrum access policy is the modeling of the dynamic behavior of channel occupancy by primary users. Under a Markovian modeling of channel occupancy, a periodic sensing and greedy access policy is known as one of the simple and practical dynamic spectrum access policies in cognitive radio networks. In this paper, the primary occupancy of each channel is modeled as a discrete-time alternating renewal process with generally distributed on- and off-periods. A periodic sensing and greedy access policy is constructed based on the general channel occupancy model. Simulation results show that the proposed policy has better throughput than the policies using channel models with exponentially distributed on- or off-periods.

• 전기전자학회논문지
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• 제22권3호
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• pp.570-577
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• 2018

With the increasing number of network nodes, traditional client/server node selection mechanisms are under tremendous pressure. In order to select efficient cooperative nodes in a highly dynamic P2P network topology, this article uses greedy algorithm to translate the overall optimization into multiple local optimal problems, and to quickly select service nodes. Therefore, the service node with the largest comprehensive capacity is selected to reduce the transmission delay and improve the throughput of the service node. The final simulation results show that the node selection strategy based on greedy algorithm can effectively improve the overall performance of P2P streaming media system.

• 한국국방경영분석학회지
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• 제13권1호
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• pp.101-115
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• 1987

This paper presents an optimization based heuristic algorithm for a tour bus scheduling problem where buses consist of various kinds of sightseeing and commutation services. First, this algorithm transforms the prolem into a vehicle routing problem on whose nodes denote trips and arcs denote connections between trips. Second, a greedy heuritic routing technique is applied to find a good feasible bus-route set. Then the greedy feasible solution is improved by the simplex method using column generation technique. The algorithm provides a better near-optimal solution which gives much reductions in the total tour distance and the number of tour buses.

• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2018년도 제58차 하계학술대회논문집 26권2호
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• pp.211-212
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• 2018

머신 러닝 환경에서 많은 양의 데이터를 한꺼번에 학습하게 되면 데이터 트래픽이 증가함에 따라 흐름 정체가 발생하고 학습 품질이 저하되며 학습속도 지연 등의 문제가 발생한다. 본 연구는 머신러닝 환경에서 빅 데이터 학습 데이터 분할을 위한 핵심 목표인 Greedy 알고리즘에 대해 설명하고 간단한 Greedy 알고리즘을 사용하여 각각의 데이터 파티션을 생성하여 학습 속도의 효율성을 향상시키는 방법을 제안한다.

• 전자공학회논문지S
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• 제35S권7호
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• pp.62-71
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• 1998

In this paper, we describe the object-oriented motioncompensation technique using the hierarchical grid interpolation(HGI). By noting that the HGI does not exploit effetively the rate-distortion (R-D) trade-off inherent in the quadtree decomposition, we propose an objectoriented HGI technique employing the greedy method. In the proposed technique, input image is decomposed in a quadtree basis using the greedy method, yielding maximum split gain in the R-D sense. Then, the motion compensation is performed using the HGI technique. The performance of the proposed technique is examined in simulation, and it will be show that the proposed technique provides better performance than the conventional object-oriented motion compensation techniques.

• 산업경영시스템학회지
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• 제36권3호
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• pp.17-24
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• 2013

Release planning in a software product line (SPL) is to select and assign the features of the multiple software products in the SPL in sequence of releases along a specified planning horizon satisfying the numerous constraints regarding technical precedence, conflicting priorities for features, and available resources. A greedy genetic algorithm is designed to solve the problems of release planning in SPL which is formulated as a precedence-constrained multiple 0-1 knapsack problem. To be guaranteed to obtain feasible solutions after the crossover and mutation operation, a greedy-like heuristic is developed as a repair operator and reflected into the genetic algorithm. The performance of the proposed solution methodology in this research is tested using a fractional factorial experimental design as well as compared with the performance of a genetic algorithm developed for the software release planning. The comparison shows that the solution approach proposed in this research yields better result than the genetic algorithm.

• 한국통신학회논문지
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• 제36권5B호
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• pp.464-470
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• 2011

V2V(Vehicle-to-Vehicle)는 VANET(Vehicular Ad-hoc Network)의 한 형태로 높은 이동성과 빈번한 토폴로지 변화로 인하여 링크 단절 문제를 야기 시킨다. 이러한 문제를 해결하기 위하여 그리디 포워딩 (greedy forwarding)과 같은 지리 기반 라우팅 프로토콜이 제안되었다. 그러나 그리디 포워딩 방식은 자신의 전송 범위 안에 속해 있는 노드들 중 목적지 노드와 가장 가까운 노드를 다음 전송 노드로 선정하기 때문에 교차로 및 차량의 진행 변화가 많은 도심 환경에서는 많은 문제점이 발생한다. 이러한 문제를 해결하기 위하여 본 논문에서는 2-hop 이웃 노드의 유/무와 도로의 특성을 고려한 GPUR(Greedy Perimeter Urban Routing) 알고리즘을 제안한다. ns-2를 사용한 성능 평가 결과 도심 환경에서 GPUR 알고리즘이 기존의 라우팅 프로토콜에 비해 경로 설정 오류 문제와 로컬 맥시멈(local maximum)에 직면할 확률을 현저히 감소시킴을 확인하였다.