• Management Science and Financial Engineering
• /
• 제18권2호
• /
• pp.13-17
• /
• 2012

Set covering has widely been accepted as a staple tool for feature selection in data mining. We present a generalized version of this classical combinatorial optimization model to make it better suited for the purpose and propose a surrogate relaxation-based procedure for its meta-heuristic solution. Mathematically and also numerically with experiments on 25 set covering instances, we demonstrate the utility of the proposed model and the proposed solution method.

• 한국컴퓨터정보학회논문지
• /
• 제20권9호
• /
• pp.21-29
• /
• 2015

The set partitioning problem is a well-known NP-hard combinatorial optimization problem, and it is formulated as an integer programming model. This paper proposes an Integer Programming-based Local Search for solving the set partitioning problem. The key point is to solve the set partitioning problem as the set covering problem. First, an initial solution is generated by a simple heuristic for the set covering problem, and then the solution is set as the current solution. Next, the following process is repeated. The original set covering problem is reduced based on the current solution, and the reduced problem is solved by Integer Programming which includes a specific element in the objective function to derive the solution for the set partitioning problem. Experimental results on a set of OR-Library instances show that the proposed algorithm outperforms pure integer programming as well as the existing heuristic algorithms both in solution quality and time.

• Journal of Information Processing Systems
• /
• 제13권5호
• /
• pp.1345-1357
• /
• 2017

A prototype selection method chooses a small set of training points from a whole set of class data. As the data size increases, the selected prototypes play a significant role in covering class regions and learning a discriminate rule. This paper discusses the methods for selecting prototypes in a classification framework. We formulate a prototype selection problem into a set covering optimization problem in which the sets are composed with distance metric and predefined classes. The formulation of our problem makes us draw attention only to prototypes per class, not considering the other class points. A training point becomes a prototype by checking the number of neighbors and whether it is preselected. In this setting, we propose a greedy algorithm which chooses the most relevant points for preserving the class dominant regions. The proposed method is simple to implement, does not have parameters to adapt, and achieves better or comparable results on both artificial and real-world problems.

• 한국컴퓨터정보학회논문지
• /
• 제11권1호
• /
• pp.11-18
• /
• 2006

LAD(Logical Analysis of Data)는 Boolean-logic에 기반을 둔 데이터 마이닝 방법론이다. LAD에 의한 데이터 분석 시 중요한 과정은 데이터 집합에 숨겨진 구조적 정보를 패턴의 형식으로 발견해내는 패턴 생성 단계이다. 기존의 패턴 생성 방법은 열거법에 기반을 두고 있어 높은 차수의 패턴을 생성하는 것은 실질적으로 불가능하였다. 본 논문에서는 최적화에 기반을 둔 패턴 생성 방법론을 제안하고 혼합 정수 선형 모형과 SCP(Set Covering Problem)의 두 가지 모형을 제안한다. 기계학습 분야에서 널리 쓰이는 데이터 집합에 대해 제안된 패턴 생성 방법을 이용한 분석 실험을 통하여 기존의 패턴 생성 방법으로는 생성될 수 없는 패턴을 쉽게 생성하는 효율성을 입증하였다.

• 한국컴퓨터정보학회논문지
• /
• 제19권10호
• /
• pp.13-21
• /
• 2014

집합 커버링 문제는 대표적인 조합 최적화 문제들 중 하나로서 n개의 열로부터 일부를 선택하여 m개의 행을 커버하되 비용을 최소화하는 문제로 정의된다. 본 논문에서는 집합 커버링 문제를 해결하기 위한 정수 계획법 기반 지역 탐색의 적용 방안을 제시하고 있다. 정수계획법 기반 지역 탐색은 이웃해를 탐색하여 현재해를 반복적으로 개선하는 지역 탐색 기법의 일종으로서 이웃해를 생성하기 위한 알고리즘으로 정수계획법을 사용한다. 본 논문에서 제시한 기법의 효과를 검증하기 위해 OR-Library의 테스트 데이터를 대상으로 실험을 수행하였다. 실험 결과, 모든 테스트 데이터에 있어서 정수계획법 기반 지역 탐색을 통해 지금까지 알려진 가장 좋은 해를 탐색할 수 있었다. 특히 4개의 테스트 데이터에 대해서는 지금까지 알려진 가장 좋은 해보다 더 좋은 해를 도출할 수 있음을 확인할 수 있었다.

• 전자공학회논문지A
• /
• 제29A권2호
• /
• pp.88-99
• /
• 1992

This paper presents an efficient method of mapping Boolean equations to a set of library gates. The proposed system performs technology mapping by graph covering. To select optimal area cover, a new cost function and local area optimization are proposed. Experimental results show that the proposed algorithm produces effective mapping using given library.

• Journal of Electrical Engineering and Technology
• /
• 제7권2호
• /
• pp.151-156
• /
• 2012

The current study presents a zero-one integer programming approach to determine the minimum break point set for the coordination of directional relays. First, the network is reduced if there are any parallel lines or three-end nodes. Second, all the directed loops are enumerated to reduce the iteration. Finally, the problem is formulated as a set-covering problem, and the break point set is determined using the zero-one integer programming technique. Arbitrary starting relay locations and the arbitrary consideration of relay sequence to set and coordinate relays result in navigating the loops many times and futile attempts to achieve system-wide relay coordination. These algorithms are compared with the existing methods, and the results are presented. The problem is formulated as a setcovering problem solved by the zero-one integer programming approach using LINGO 12, an optimization modeling software.

• 한국경영과학회지
• /
• 제37권4호
• /
• pp.197-209
• /
• 2012

This paper studies an emergency service vehicle location problem, where minimum reliability level pre-specified at each demand point is assured. Several models are suggested depending on the busy fraction, which is the time proportion of unavailability for the ambulances. In this paper a new model on computing the busy fraction is suggested, where it varies depending on the distance between the demand point and ambulances, hence it may respond the more realistic situation. The busy fraction for the ambulance location determined by the optimization model is computed by the simulation, and updated through the iterative procedure. It has been shown that the performances of the solutions obtained by the algorithm suggested for the instances appeared in the literature.

• Asian Journal of Innovation and Policy
• /
• 제8권1호
• /
• pp.122-140
• /
• 2019

Providing free primary care to everyone is an important goal pursued by many countries under universal health care programs. Countries like India need to efficiently utilize their limited capacities towards this purpose. Unfortunately, due to a variety of reasons, patients incur substantial travel and out-of-pocket expenses for getting primary care from publicly-funded facilities. We propose a set-covering optimization model to assist health policy-makers in managing existing capacity in a better way. Decision-making should consider upgrading centers with better potential to reduce patient expenses and reallocating capacities from less preferred facilities. A multinomial logit choice model is used to predict the preferences. In this article, a brief background and literature survey along with the mixed integer linear programming (MILP) optimization model are presented. The working of the model is illustrated with the help of numerical experiments.

• 정보처리학회논문지:소프트웨어 및 데이터공학
• /
• 제5권10호
• /
• pp.483-488
• /
• 2016

본 논문은 최근접 이웃 규칙을 이용한 프로토타입을 이용하는 분류 학습을 제안한다. 훈련 데이터가 대표하는 클래스 영역을 초월구로 분할하는데 최근접 이웃규칙을 적용시키며, 초월구는 동일 클래스 데이터들만 포함시킨다. 초월구의 반지름은 가장 인접한 다른 클래스 데이터와 가장 먼 동일 클래스 데이터의 중간 거리 값으로 결정한다. 그리고 전체 훈련 데이터를 대표하는 최소의 프로토타입 집합을 선택하기 위해 집합 덮개 최적화를 이용한다. 제안하는 선택 방법은 클래스 별 프로토타입을 선택하는 그리디 알고리즘으로 설계되며, 대규모 훈련 데이터에 대한 병렬처리가 가능하다. 분류 예측은 최근접 이웃 규칙을 이용하며, 새로운 훈련 데이터는 프로토타입 집합이다. 실험에서 제안하는 방법은 기 연구된 학습 방법에 비해 일반화 성능이 우수하다.