• Journal of applied mathematics & informatics
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• 제26권3_4호
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• pp.493-500
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• 2008

In this paper, we first construct a mathematical model for tagSNP selection based on LD measure $r^2$, then aiming at this kind of model, we develop an efficient algorithm, which is called approximate greedy algorithm. This algorithm is able to make up the disadvantage of the greedy algorithm for tagSNP selection. The key improvement of our approximate algorithm over greedy algorithm lies in that it adds local replacement(or local search) into the greedy search, tagSNP is replaced with the other SNP having greater similarity degree with it, and the local replacement is performed several times for a tagSNP so that it can improve the tagSNP set of the local precinct, thereby improve tagSNP set of whole precinct. The computational results prove that our approximate greedy algorithm can always find more efficient solutions than greedy algorithm, and improve the tagSNP set of whole precinct indeed.

• 융합신호처리학회논문지
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• 제3권3호
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• pp.63-69
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• 2002

디테일드 라우팅은 VLSI 설계 과정중의 하나로, 글로벌 라우팅을 수행한 후 각 라우팅 영역에 할당된 네트들을 트랙에 할당하여 구체적인 네트들의 위치를 결정하는 문제이며, 디테일드 라우팅에서 최적의 해를 얻기 위해 left-edge 알고리즘, dogleg 알고리즘, greedy 채널 라우팅 알고리즘등이 이용된다 본 논문에서는 디테일드 라우팅 문제에 대하여 유전자 알고리즘(genetic algorithm; GA)을 이용한 해 공간 탐색(solution space search) 방식을 제안하였으며, 제안한 방식을 greedy 채널 라우팅 알고리즘과 비교, 분석하였다.

• 한국시뮬레이션학회논문지
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• 제28권1호
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• pp.67-79
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• 2019

다기능레이더(MFR)를 장착한 함정의 작전수행은 적의 위협에 대한 징후를 바탕으로 위협의 정도를 판단하고 이를 바탕으로 MFR 자원을 위협별로 할당하는 것으로 작전을 시작한다. 본 연구는 MFR 탐지체계를 가진 함정의 임무 시작 시 필요한 위협별 MFR 자원할당 문제에 대하여 시뮬레이션을 이용한 기법과 Greedy 기법을 이용한 MFR 자원할당 방안을 제시하여 그 결과를 비교분석하였다. 분석시 자원할당에 따른 탐지확률 함수가 선형인 경우와 지수형인 경우를 고려하여 실험을 수행하였다. 실험 결과 시뮬레이션 기법과 Greedy기법의 결과는 서로 비슷한 자원할당 결과를 보여주고 있으며, Greedy 기법은 시뮬레이션 기법에 비하여 그 수행시간이 아주 짧아 실제 임무 수행 시에 이용 가능한 기법으로 판단된다. 여러 가지 위협의 정도에 대해 Greedy 기법을 이용하여 MFR 자원할당 결과를 분석하였다.

• 한국통신학회논문지
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• 제33권12B호
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• pp.1075-1082
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• 2008

그리디 포워딩(Greedy forwarding) 기법은 주변 노드들의 정보만을 이용해 패킷을 전달하는 기법으로, 전체 라우팅 경로를 유지해야 하는 다른 애드혹 라우팅 프로토콜에 비해 경로 유지가 쉽기 때문에 토폴로지가 자주 변하는 차량간 애드혹 네트워크에 적합한 방식이라고 할 수 있다. 그리디 포워딩 기법에서는 주기적인 비콘 전송을 통해 이웃 노드들의 위치를 획득하고, 패킷을 전달할 때 수신 노드와 가장 가까운 노드를 전달 노드로 선택한다. 이러한 그리디 포워딩의 성능을 떨어뜨리는 주요 원인 중 하나는 이웃 노드가 원래의 위치에서 벗어나면서 발생하는 링크 단절 문제이다. 본 논문에서는 그리디 포워딩 기반의 라우팅 프로토콜인 Greedy Perimeter Stateless Routing (GPSR) 프로토콜을 바탕으로 링크 단절 문제를 해결하기 위한 새로운 알고리즘을 제안한다. 제안하는 알고리즘은 이웃 노드의 위치와 비콘을 수신한 시간 등을 고려해 효율적이면서도 안정적인 라우팅 경로를 찾는 것을 목표로 한다. 다양한 환경에서의 실험 결과를 통해 우리는 제안하는 알고리즘이 GPSR과 기존의 연구 결과들에 비해 더 뛰어난 성능을 보이는 것을 확인하였다.

• 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.

• 한국정보처리학회논문지
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• 제7권3호
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• pp.935-942
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• 2000

In this paper we introduce a fast simplification algorithm for terrain height fields to produce a triangulated irregular network, based on the greedy insertion algorithm in [1,4,5]. Our algorithm partitions a terrain height data into rectangular blocks with the same size ad simplifies blocks one by one with the greedy insertion algorithm. Our algorithm references only to the points and the triangles withing each current block for adding a point into the triangulation. Therefore, the algorithm runs faster than the greedy insertion algorithm, which references all input points and triangles in the terrain. Our experiment shows that partitioning method runs from 4 to more than 20 times faster, and it approximates test height fields as accurately as the greedy insertion algorithms. Most greedy insertion algorithms suffer from elongated triangles that usually appear near the boundaries. However, we insert the four corner points into each block to produce the base triangulation of the block before the point addition step begins so that elongated triangles could not appear in th simplified terrain.

• 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.

• Journal of Information Processing Systems
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• 제10권3호
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• pp.471-482
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• 2014

Influence maximization is an important problem of finding a small subset of nodes in a social network, such that by targeting this set, one will maximize the expected spread of influence in the network. To improve the efficiency of algorithm KK_Greedy proposed by Kempe et al., we propose two improved algorithms, Lv_NewGreedy and Lv_CELF. By combining all of advantages of these two algorithms, we propose a mixed algorithm Lv_MixedGreedy. We conducted experiments on two synthetically datasets and show that our improved algorithms have a matching influence with their benchmark algorithms, while being faster than them.

• 한국군사과학기술학회지
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• 제23권4호
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• pp.381-388
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• 2020

Weapon target assignment problem is an essential technology for automating the operator's rapid decision-making support in a battlefield situation. Weapon target assignment problem is a kind of the optimization problem that can build up an objective function by maximizing the number of threat target destructed or maximizing the survival rate of the protected assets. Weapon target assignment problem is known as the NP-Complete, and various studies have been conducted on it. Among them, a greedy heuristic algorithm which guarantees (1-1/e) approximation has been considered a very practical method in order to enhance the applicability of the real weapon system. In this paper, we formulated the weapon target assignment problem for supporting decision-making at the level of artillery. The lazy strategy based on hierarchical structure is proposed to accelerate the greedy algorithm. By experimental results, we show that our algorithm is more efficient in processing time and support the same level of the objective function value with the basic greedy algorithm.

• 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.