• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 2002년도 춘계공동학술대회
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• pp.23-30
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• 2002

본 연구는 추가제약이 있는 최소 신장나무 문제(Constrained Minimum Spanning Tree : CMST문제)에 대한 유사다항시간 알고리듬 및 근사 해법 개발에 관한 것이다. CMST문제는 NP-hard문제임이 이미 증명되었으며, 이후 이 문제에 대해서는 근사해법 개발이 주된 관심이 되어왔다 [Ravi and Goemans 96]는 다항시간 근사 해법(PTAS)을 이미 개발하였고, [Marathe et at 98]은 가능해(feasible solution)는 아니지만, 앞으로 서술할 $(1+1/\varepsilon,\;+\epsilon)$사해를 구하는 완전다항시간 근사해법 (FPTAS)을 제시하였다. 이와는 달리 [Papa. and Yan, 00]는 파레토 근사 최적해를 구하는 FPTAS를 제시하였는데, 본 연구는 이들의 연구에서 주로 의존하고 있는 행렬-나무 정리(Tree-Matrix Theorem)를 보다 일반화하여, CMST문제에 대한 유사다항시간 알고리듬과 $(1+\varepsilon,\;1+\epsilon)$근사해를 구하는 FPTAS를 제시할 것이다.

• Journal of Information Technology Applications and Management
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• 제14권3호
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• pp.227-236
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• 2007

Students in cyber universities can take every course because there are no physical constraints such as class rooms. On the other hand. cyber universities should take a heavy burden to schedule real-time exams in a designated time period. Any two courses a student takes must not be simultaneously allocated to a time slot in such a schedule. It is well known that the complexity of this kind of scheduling problem increases exponentially as the number of courses does. This research provides a heuristic method to make on-line real-time exam timetables with minimal exam time span. It considers the constraint of not allocating courses a student takes to simultaneous exam time and prioritizes courses by the number of students.

• 산업경영시스템학회지
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• 제18권36호
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• pp.143-152
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• 1995

This paper determines the allocation of computers and data files to minimize the sum of processing and communication costs which occur in processing jobs at each node. The problem of optimally configuring a distributed computer system belongs to the class of NP-Complete problems and the object function of this paper is nonlinear function and is hard to solve. This paper seeks the solution of distributed processing system by Tabu Search. Firstly, it presents the method of generating the starting solution proper to the distributed processing system. Secondly, it develops the method of searching neighborhood solutions. Finally, it determines the Tabu restriction appropriate to the distributed processing system. According to the experimental results, this algorithm solves a sized problems in reasonable time and is effective in the convergence of the solution. The algorithm developed in this paper is also applicable to the general allocation problems of the distributed processing system.

• 산업경영시스템학회지
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• 제34권3호
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• pp.90-96
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• 2011

Finding the critical path (or the longest path) on acyclic directed graphs, which is well-known as PERT/CPM, the ambiguity of each acr's length can be modeled as a range or an interval, in which the actual length of arc may realize. In this case, the min-max regret criterion, which is widely used in the decision making under uncertainty, can be applied to find the critical path minimizing the maximum regret in the worst case. Since the min-max regret critical path problem with the interval arc's lengths is known as NP-hard, this paper proposes a heuristic algorithm to diminish the maximum regret. Then the computational experiments shows the proposed algorithm contributes to the improvement of solution compared with the existing heuristic algorithms.

• 대한산업공학회지
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• 제29권3호
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• pp.222-229
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• 2003

In this paper, we address a layout design problem, PTN[2], for determining an appropriate 2-class-based dedicated storage layout in a class of unit load storage systems. Our strong conjecture is that PTNI2] is NP-hard. Restricting PTN[2], we provide three solvable cases of PTN[2] in which an optimal solution to the solvable cases is one of the partitions based on the PAI(product activity index)-nonincreasing ordering. However, we show with a counterexample that a solution based on the PAI-non increasing ordering does not always give an optimal solution to PTN[2]. Utilizing the derived properties, we construct an effective heuristic algorithm for solving PTN[2] based on a PAI-non increasing ordering with performance ratio bound. Our algorithm with O($n^2$) is effective in the sense that it guarantees a better class-based storage layout than a randomized storage layout in terms of the expected single command travel time.

• 대한산업공학회지
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• 제16권1호
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• pp.17-25
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• 1990

Most of the least cost transportation network design problems are frequently formulated as the minimum spanning arborescence problems in directed networks with bitype are costs. These costs are classified whether the arc is included in the path from the root to a specified node over a given spanning arborescence. We prove that this problem is NP-hard, and develop a polynomial time algorithm for acyclic networks. The probelm in acyclic networks is initially formulated as 0-1 integer programming. Next, we prove that the 0-1 relaxed linear programming has an integral optimum solution by complementary slackness conditions. In this paper, we present an $O(n^2)$ algorithm based on a shortest path algorithm.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2012년도 추계학술발표대회
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• pp.280-281
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• 2012

클라우드 기술이 발달하면서 사용자 요구를 만족하면서도 비용을 절감하기 위해 VM 의 개수를 자동으로 조절해주는 오토스케일링 기술이 부각되었다. 하지만 어떤 VM 을 추가할 것인지는 NP-Hard Problem 으로 휴리스틱하게 풀 수밖에 없다. 따라서 사용자의 실시간으로 변하는 요구에 바로 대처하지 못할 수 있다. 사용자 요구에 실시간적으로 대처하기 위해서는 사용자가 보내는 요청의 패턴을 읽고, 앞으로 올 요청을 미리 아는 기술이 필요하다. 이에 본 논문에서는 리퀘스트 예측을 통한 오토스케일링을 가능케 하도록 구조를 제안하고자 한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권11호
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• pp.4355-4371
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• 2020

Phase retrieval, recovering a signal from phaseless measurements, is generally considered to be an NP-hard problem. This paper adopts an amplitude-based nonconvex optimization cost function to develop a new stochastic gradient algorithm, named stochastic reweighted phase retrieval (SRPR). SRPR is a stochastic gradient iteration algorithm, which runs in two stages: First, we use a truncated sample stochastic variance reduction algorithm to initialize the objective function. The second stage is the gradient refinement stage, which uses continuous updating of the amplitude-based stochastic weighted gradient algorithm to improve the initial estimate. Because of the stochastic method, each iteration of the two stages of SRPR involves only one equation. Therefore, SRPR is simple, scalable, and fast. Compared with the state-of-the-art phase retrieval algorithm, simulation results show that SRPR has a faster convergence speed and fewer magnitude-only measurements required to reconstruct the signal, under the real- or complex- cases.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2020년도 춘계학술발표대회
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• pp.44-46
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• 2020

Aggregating data with an optimal delay, which is a critical problem in Wireless Sensor Networks applications, is proven as NP-hard. In this paper, we focus on optimizing the aggregation delay by presenting an idea for channel and timeslot co-scheduling data aggregation in MWSNs. The proposed scheme, which names Break and Join, maximizes the number of sensor nodes to be scheduled in a working period, so that the overall number of working periods and data collection delay are reduced.

• 한국콘텐츠학회논문지
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• 제9권12호
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• pp.52-63
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• 2009

본 논문에서는 유니폼 멀티프로세서 환경에서 단순 주기성 태스크 시스템을 성공적으로 스케줄 할 수 있는 알고리즘을 제안한다. 멀티프로세서 환경에서 주기성 태스크를 스케줄하기 위한 파티션드(partitioned) 스케줄링 알고리즘은 bin-packing 문제와 같은 문제로써 해결하는 게 불가능하다고 알려져 있다. 본 논문에서는 "task-splitting"기법을 이용하여 단순 주기성 태스크 시스템을 다른 단순 주기성 태스크 시스템으로 변환하는 글로벌(global) 스케줄링 알고리즘을 제시하고, 변환과정을 거친 단순 주기성 태스크 시스템은 유니폼 멀티프로세서에서 파티션드 스케줄링 알고리즘에 의해 성공적으로 스케줄 된다. 그리고 유니폼 멀티프로세서 환경에서 제안한 알고리즘이 이론적으로 최대 이용률 범위(utilization bound)까지 성공적으로 스케줄 할 수 있음을 증명한다.