• 한국컴퓨터정보학회논문지
• /
• 제15권5호
• /
• pp.39-47
• /
• 2010

제약 만족 최적화 문제는 복잡한 제약 조건을 포함하는 동시에 비용을 최소화하는 최적화 문제로 정의된다. 지역 탐색과 제약 프로그래밍은 각각 이와 같은 문제의 해결을 위한 도구로서 활용되어 왔다. 본 논문에서는 탐색 성능 향상을 위해 지역 탐색과 제약 프로그래밍을 결합하는 방안을 제시하고 있다. 기본적으로 대상 문제의 해결을 위해 지역 탐색을 사용한다. 그러나 지역 탐색만을 사용할 경우 제약 조건을 모두 만족하는 실행 가능한 이웃해를 생성하는 것이 매우 힘들어진다. 따라서 본 논문에서는 이웃해 생성을 위한 도구로 제약 프로그래밍을 도입하였다. 가중치가 부여된 N-Queens 문제를 대상으로 한 실험 결과, 본 논문에서 제시한 방법을 통해 탐색 성능을 획기적으로 향상시킬 수 있음을 확인할 수 있었다.

• 대한기계학회:학술대회논문집
• /
• 대한기계학회 2001년도 춘계학술대회논문집B
• /
• pp.706-711
• /
• 2001

This paper represents a relaxation matching algorithm based on global structure constraint satisfaction. Relaxation matching algorithm is a conventional approach to the matching problem. However, we confronted some problems such as null-matching and multi-matching problems by just using the relaxation matching technique. In order to solve the problems, in this paper, the matching problem is regarded as constraint satisfaction problem, and a relaxation matching algorithm is proposed based on global structure constraint satisfaction. The proposed algorithm is applied a landslide picture to show the effectiveness. When the algorithm is processed at landslide inspecting and monitoring system, motion parameters such as displacement area and its direction are computed. Once movement is recognized, displacements are estimated graphically with statistical amount in the image plane. Simulation has been done to prove the proposed algorithm by using time-sequence image of landslide inspection and monitoring system.

• 산업경영시스템학회지
• /
• 제25권2호
• /
• pp.92-101
• /
• 2002

The Job Shop Scheduling Problem(JSSP) is concerned with schedule of m different machines and n jobs where each job consists of a chain of operations, each of which needs to be processed during an uninterrupted time period of a given length on a given machine. The purpose of this paper is to develop the efficient heuristic method for solving the minimum makespan problem of the large scale job shop scheduling. The proposed heuristic method is based on a Tabu Search(TS) and on a Constraint Satisfaction Technique(CST). In this paper, ILOG libraries is used to embody the job shop model, and a CST is developed for this model to generate the increased solution. Then, TS is employed to overcome the increased search time of CST on the increased problem size md to refine the next-current solution. Also, this paper presents the new way of finding neighbourhood solution using TS. On applying TS, a new way of finding neighbourhood solution is presented. Computational experiments on well known sets of MT and LA problem instances show that, in several cases, our approach yields better results than the other heuristic procedures discussed In literature.

• 한국정밀공학회:학술대회논문집
• /
• 한국정밀공학회 1997년도 춘계학술대회 논문집
• /
• pp.589-594
• /
• 1997

We have already presented the constraint satisfaction algorithm which could solve the losed loop problem in constraint network by using local constraint propagation, variable elimination and constraint modularization. With this algorithm, we have implemented a knowledge-based system (intelligent CAD) for supporting machine design interactively. In this paper, we present newer constraint satisfaction algorithm which can solve inequalities or under-constrained problems in constraint network, interactively and efficiently. This algorithm is a hybrid type of using both declarative description (constraint represention) and optimization algorithm (Simulated Annealing), simultaneously. The under-constrained problems are represented by constraint networks and satisfied completely with this algorithm. The usefulness of our algorithm will be illustrated by the application to a gear design.

• 한국컴퓨터정보학회논문지
• /
• 제22권9호
• /
• pp.9-16
• /
• 2017

The course timetabling problem is a problem assigning a set of subjects to the given classrooms and different timeslots, while satisfying various hard constraints and soft constraints. This problem is defined as a constraint satisfaction optimization problem and is known as an NP-complete problem. Various methods has been proposed such as integer programming, constraint programming and local search methods to solve a variety of course timetabling problems. In this paper, we propose an iterative improvement search method to solve the problem based on constraint programming. First, an initial solution satisfying all the hard constraints is obtained by constraint programming, and then the solution is repeatedly improved using constraint programming again by adding new constraints to improve the quality of the soft constraints. Through experimental results, we confirmed that the proposed method can find far better solutions in a shorter time than the manual method.

• 대한안전경영과학회지
• /
• 제6권2호
• /
• pp.141-154
• /
• 2004

The objective of this paper is to develop the efficient heuristic method for solving the minimum makespan problem of the job shop scheduling. The proposed heuristic method is based on a constraint satisfaction problem technique and a improved randomizing search algorithm. In this paper, ILOG programming libraries are used to embody the job shop model, and a constraint satisfaction problem technique is developed for this model to generate the initial solution. Then, a improved randomizing search algorithm is employed to overcome the increased search time of constrained satisfaction problem technique on the increased problem size and to find a improved solution. Computational experiments on well known MT and LA problem instances show that this approach yields better results than the other procedures.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• 제12권1호
• /
• pp.77-85
• /
• 2012

This paper describes a novel approach to adaptive courseware generation. This approach adopts its structure from existing intelligent tutoring systems and introduces a new component called pedagogical scenario model to support pedagogical flexibility in the adaptation process of courseware generation system. The adaptation is carried out using Dynamic Constraint Satisfaction Problem framework, which is a variant of classical Constraint Satisfaction Problem, to deliver courseware tailored to individual learner. Such a framework provides a high level of expressiveness to deal with the particular characteristics of courseware generation problem. Further, it automatically designs a sound courseware satisfying the design constraints imposed by the domain, the pedagogical scenario and learner models.

• 한국정보처리학회:학술대회논문집
• /
• 한국정보처리학회 2006년도 추계학술발표대회
• /
• pp.55-58
• /
• 2006

This paper presents solving the Sudoku puzzle as a constraint satisfaction problem (CSP). After introducing the rules and characteristics of the puzzle, we formulate the puzzle as a CSP and develop various methods of solving the problem. Blind search, minimum remaining value (MRV) heuristic, and some advanced methods are investigated, and their algorithms are implemented in this undergraduate project. The performance comparisons of these methods are discussed in the paper.

• 산업기술연구
• /
• 제19권
• /
• pp.91-99
• /
• 1999

The dock is the most important resource in shipbuilding yard. Among the shipbuilding schedules, the ship erection schedule in a dock is preferentially built. As results of it, the other schedules(machining in plants, block assembly, pre-painting, pre-rigging, painting and etc) are made. In this study, ship erection scheduling is formulated using ILOG Scheduler. This study is to develop a new problem solving method for ship erection to make an effective schedule based on Constraint Satisfaction Technique(CST).

• 지능정보연구
• /
• 제6권2호
• /
• pp.1-14
• /
• 2000

컨테이너 터미널에서의 선석 및 크레인 일정계획은 일정 기간 동안 입항 예정인 선박들을 대상으로 선석을 배정하고 접안 시기와 기간을 결정하며, 또한 각 선박별로 컨테이너를 싣고 내릴 크레인을 배정하되 각 크레인의 서비스 시작과 완료시간까지 지정하는 전 과정을 포함한다. 이 문제는 본적으로 서로 시간적 공간적으로 복잡한 제약 관계에 있는 여러 선석들과 크레인들을 충돌 없이 각 선박에 할당하여야 하는 제약조건 만족 문제인 동시에, 각 선박의 희망 입출항 시간을 최대한 존중하면서 터미널의 운영비용을 최소화할 수 있는 계획안을 도출해야 하는 최적화 문제이기도 하 다. 본 논문에서는 이 문제의 해결을 위해 제약만족 탐색기법을 동원하여 먼저 제약조건을 만족하는 해를 찾은 뒤, 제약조건을 만족하는 범위 내에서 보다 최적의 해를 유도해 내기 위해 휴리스틱 교정 기법을 제약만족 탐색기법의 틀 내에서 반복적으로 적용하는 방안을 제시하고 있다. 실제 부산 신선대 컨테이너 터미널의 데이터를 이용한 실험 결과 현장 전문가가 만족할 만한 수준의 일정 계획을 신속하게 수립할 수 있음을 확인하였다.