• 제목/요약/키워드: dynamic programming

검색결과 952건 처리시간 0.105초

부분서열정렬 개선 기법을 사용한 효율적인 복수서열정렬에 관한 알고리즘 (An Efficient Method for Multiple Sequence Alignment using Subalignment Refinement)

  • 김진;정우철;엄상용
    • 한국정보과학회논문지:소프트웨어및응용
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    • 제30권9호
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    • pp.803-811
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    • 2003
  • 단백질들의 복수서열정렬은 단백질 서열간의 관계를 유추할 수 있는 유용한 도구이다. 최적화된 복수서열정렬을 얻기 위해 사용되는 가장 유용한 방법은 dynamic programming이다. 그러나 dynamic programming은 특정한 비용함수를 사용할 수 없기 때문에 특별한 경우 최소의 비용을 가지는 복수서열 정렬을 제공하지 못하는 문제점이 있다. 우리는 이러한 문제점을 해결하기 위하여 부분서열정렬 개선기법을 사용한 알고리즘을 제안하였으며, 이 알고리즘이 dynamic programming의 문제점을 효과적으로 해결함을 보였다.

복수 염기서열 정렬을 위한 한 유용성 알고리즘 (An effcient algorithm for multiple sequence alignment)

  • 김진;송민동
    • 한국정보과학회:학술대회논문집
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    • 한국정보과학회 1998년도 가을 학술발표논문집 Vol.25 No.2 (2)
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    • pp.51-53
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    • 1998
  • 3개 이상의 DNA 혹은 단백질의 염기서열을 정렬하는 복수 염기서열 정렬(multiple sequence alignment)방법은 염기서열들 사이의 진화관계, gene regulation, 단백질의 구조와 기능에 관한 연구에 필수적인 도구이다. 복수 염기서열 정렬문제는 NP-complete 문제군에 속하며, 이 문제를 해결하기 위하여 가장 유용하게 사용되는 알고리즘으로는 dynamic programming이 있다. Dynamic programming은 주어진 입력 염기서열 군들에 대한 최적의 정렬을 생산할 수 있다. 그러나 dynamic programming의 단점은 오랜 실행시간이 요구되며, 때로는 dynamic programming의 속성 때문에 이 알고리즘을 사용하여도 주어진 입력 염기서열 군들에 대한 최적의 정렬을 얻어내지 못하는 경우가 있다. 본 연구에서는 이러한 dynamic programming의 문제를 해결하기 위하여 genetic algorithm을 복수 염기서열 정렬문제에 적용하였다. 본 논문에서는 genetic algorithm의 design과 적용방법을 기술하였다. 본 연구에서 제안된 genetic algorithm을 사용하여 dynamic programming의 단점이었던 오랜 실행시간을 줄일 수 있었으며, dynamic programming이 제공하지 못하는 최적의 염기서열 정렬을 제공할 수 있었다.

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Multiple dynamic programming에 관한 연구 (A Study of Multiple Dynamic Programming)

  • 박영문
    • 전기의세계
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    • 제21권1호
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    • pp.13-16
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    • 1972
  • Dynamic Programming is regarded as a very powerful tool for solving nonlinear optimization problem subject to a number of constraints of state and control variables, but has definite disadvantages that it requires much more computing time and consumes much more memory spaces than other technigues. In order to eliminate the above-mentioned demerits, this paper suggests a news technique called Multiple Dynamic Programming. The underlying principles are based on the concept of multiple passes that, instead of forming fin lattices in time-state plane as adopted in the conventional Dynamic Programming, the Multiple Dynamic Programming constitutes, at the first pass, coarse lattices in the feasible domain of time-state plane and determines the optimal state trajectory by the usual method of Dynamic Programming, and at the second pass again constitutes finer lattices in the narrower domain surrounded by both the upperand lower edges next to the lattice edges through which the first pass optimal trajectory passes and determines the more accurate optimal trajectory of state, and then at the third pass repeats the same processes, and so on. The suggested technique insures remarkable curtailment in amounts of computer memory spaces and conputing time, and its applicability has been demonstrated by a case study on the hydro-thermal power coordination in Korean power system.

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동적계획모형을 이용한 근무형태 결정 (Determination of Work Schedule Type by Dynamic Programming)

  • 김중순;안봉근;손달호
    • 경영과학
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    • 제20권2호
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    • pp.33-43
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    • 2003
  • In this paper we applied dynamic programming to determining work schedule type. In dynamic programming formulation, each day during a planning horizon represents a stage for which a decision is made. The alternatives are given by work schedule types that combine regular time, overtime, additional shift, and so on. In this case, their associated return function is labor cost. The state is defined as the amount of work time allocated to stage 1, stage 2,…, and current stage. A case study for a real manufacturing company was performed to apply dynamic programming to scheduling daily work hours during a week. The case study showed that total cost of our solution derived from dynamic programming decreased by about 6% as compared with the solution obtained from the previous method.

Approximate Dynamic Programming Strategies and Their Applicability for Process Control: A Review and Future Directions

  • Lee, Jong-Min;Lee, Jay H.
    • International Journal of Control, Automation, and Systems
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    • 제2권3호
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    • pp.263-278
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    • 2004
  • This paper reviews dynamic programming (DP), surveys approximate solution methods for it, and considers their applicability to process control problems. Reinforcement Learning (RL) and Neuro-Dynamic Programming (NDP), which can be viewed as approximate DP techniques, are already established techniques for solving difficult multi-stage decision problems in the fields of operations research, computer science, and robotics. Owing to the significant disparity of problem formulations and objective, however, the algorithms and techniques available from these fields are not directly applicable to process control problems, and reformulations based on accurate understanding of these techniques are needed. We categorize the currently available approximate solution techniques fur dynamic programming and identify those most suitable for process control problems. Several open issues are also identified and discussed.

제어를 위한 동적 프로그래밍에 관한 연구 (A Study on the Dynamic Programming for Control)

  • 조항덕;김우식
    • 한국소음진동공학회:학술대회논문집
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    • 한국소음진동공학회 2007년도 추계학술대회논문집
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    • pp.556-559
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    • 2007
  • The notion of linearity is fundamental in science and engineering. Much of system and control theory is based on the analysis of linear system, which does not care whether it is nonlinear and complex. The dynamic programming is one of concerned technology when users are interested in choosing best choice from system operation for nonlinear or dynamic system‘s performance and control problem. In this paper, we will introduce the dynamic programming which is based on discrete system. When the discrete system is constructed with discrete state, transfer between states, and the event to induct transfer, the discrete system can describe the system operation as dynamic situation or symbolically at the logical point of view. We will introduce technologies which are related with controllable of Controlled Markov Chain as shown example of simple game. The dynamic programming will be able to apply to optimal control part which has adaptable performance in the discrete system.

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An Approach of Solving the Constrained Dynamic Programming - an Application to the Long-Term Car Rental Financing Problem

  • Park, Tae Joon;Kim, Hak-Jin;Kim, Jinhee
    • 한국컴퓨터정보학회논문지
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    • 제26권12호
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    • pp.29-43
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    • 2021
  • 본 연구에서 제약식프로그래밍을 이용하여 제약식 있는 동적계획법 모형을 푸는 한 방법을 제시한다. 현재 제약식 있는 동적계획법을 다루는 방법은 각 단계별 제약식들의 상태를 일반적인 동적계획법의 상태공간에 추가하여 마치 제약식이 없는 동적계획법 방식을 적용하는데 반해, 이 연구에서 제시하는 방식은 제약식의 상태가 제약식프로그래밍의 변수 도메인으로 표현되고 저장된다. 계산에 있어서도 일반적인 동적계획법의 벨만방정식의 해법과 함께 제약식을 다루기 위한 제약식프로그래밍의 확산-추론 방법을 사용하는 하이브리드 방식을 따른다. 이 두가지 방식의 비교를 위해 특별히 장기 자동차 렌탈 문제를 제시하고 이 문제의 단순화된 모형을 중심으로 다른 방식으로 해결하는 과정을 보고 그 장단점을 논한다.

최소절단손실(最小切斷損失)에 의한 최적생산(最適生産)길이의 선정(選定)에 대한 동적계획법응용(動的計劃法應用) (An Application of Dynamic Programming to the Selection of Optimal Production Lengths Based on the Minimum Cutting Loss)

  • 조규갑
    • 대한산업공학회지
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    • 제4권2호
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    • pp.77-81
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    • 1978
  • The assortment problem with deterministic demand has been formulated so that a dynamic programming can be applied to find optimal production lengths that will minimize the sum of cutting losses. The original minimization problem can be reformulated as the maximization problem with a different objective function. This problem can be solved by the dynamic programming technique. A numerical example illustrates this approach. The ratio of computation amount of emumeration method to that of this dynamic programming is approximately n to 1.

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동적 계획법을 이용한 스테레오 대응 알고리즘 (Stereo Correspondence Algorithm Using Dynamic programming)

  • 이충환;홍석교
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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    • pp.310-310
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    • 2000
  • The main problem in stereo vision is to find corresponding points in left and right image known as correspondence problem. Once correspondences determined, the depth information of those points are easily computed form the pairs of points in both image. In this paper, dynamic programming considering half-occluded region is used fer solving correspondence problem.

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