• Journal of the Korea Society of Computer and Information
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• v.26 no.12
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• pp.29-43
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• 2021

In this paper, a new approach to solve the constrained dynamic programming is proposed by using the constraint programming. While the conventional dynamic programming scheme has the state space augmented with states on constraints, this approach, without state augmentation, represents states of constraints as domains in a contraining programming solver. It has a hybrid computational mechanism in its computation by combining solving the Bellman equation in the dynamic programming framework and exploiting the propagation and inference methods of the constraint programming. In order to portray the differences of the two approaches, this paper solves a simple version of the long-term car rental financing problem. In the conventional scheme, data structures for state on constraints are designed, and a simple inference borrowed from the constraint programming is used to the reduction of violation of constraints because no inference risks failure of a solution. In the hybrid approach, the architecture of interface of the dynamic programming solution method and the constraint programming solution method is shown. It finally discusses the advantages of the proposed method with the conventional method.

• IE interfaces
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• v.12 no.3
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• pp.362-373
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• 1999

Resource Constrained Dynamic Multi-Projects Scheduling (RCDMPS) is intended to schedule activities of two or more projects sequentially arriving at die shop under restricted resources. The aim of this paper is to develop a new problem solving method for RCDMPS to make an effect schedule based by constraint programming. The constraint-based scheduling method employs ILOG Solver which is C++ constraint reasoning library for solving complex resource management problems and ILOG Schedule which is a add-on library to ILOG Solver dedicated to solving scheduling problems. And this method interfaces with ILOG Views so that the result of scheduling displays with Gantt chart. The scheduling method suggested in this paper was applied to a company scheduling problem and compared with the other heuristic methods, and then it shows that the new scheduling system has more preference.

• Journal of Intelligence and Information Systems
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• v.17 no.3
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• pp.43-61
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• 2011

In this research, we propose a dynamic decision making using social context based on ontology. Dynamic adaptation is adopted for the high qualified decision making, which is defined as creation of proper information using contexts depending on decision maker's state of affairs in ubiquitous computing environment. Thereby, the context for the dynamic adaptation is classified as a static, dynamic and social context. Static context contains personal explicit information like demographic data. Dynamic context like weather or traffic information is provided by external information service provider. Finally, social context implies much more implicit knowledge such as social relationship than the other two-type context, but it is not easy to extract any implied tacit knowledge as well as generalized rules from the information. So, it was not easy for the social context to apply into dynamic adaptation. In this light, we tried the social context into the dynamic adaptation to generate context-appropriate personalized information. It is necessary to build modeling methodology to adopt dynamic adaptation using the context. The proposed context modeling used ontology and cases which are best to represent tacit and unstructured knowledge such as social context. Case-based reasoning and constraint satisfaction problem is applied into the dynamic decision making system for the dynamic adaption. Case-based reasoning is used case to represent the context including social, dynamic and static and to extract personalized knowledge from the personalized case-base. Constraint satisfaction problem is used when the selected case through the case-based reasoning needs dynamic adaptation, since it is usual to adapt the selected case because context can be changed timely according to environment status. The case-base reasoning adopts problem context for effective representation of static, dynamic and social context, which use a case structure with index and solution and problem ontology of decision maker. The case is stored in case-base as a repository of a decision maker's personal experience and knowledge. The constraint satisfaction problem use solution ontology which is extracted from collective intelligence which is generalized from solutions of decision makers. The solution ontology is retrieved to find proper solution depending on the decision maker's context when it is necessary. At the same time, dynamic adaptation is applied to adapt the selected case using solution ontology. The decision making process is comprised of following steps. First, whenever the system aware new context, the system converses the context into problem context ontology with case structure. Any context is defined by a case with a formal knowledge representation structure. Thereby, social context as implicit knowledge is also represented a formal form like a case. In addition, for the context modeling, ontology is also adopted. Second, we select a proper case as a decision making solution from decision maker's personal case-base. We convince that the selected case should be the best case depending on context related to decision maker's current status as well as decision maker's requirements. However, it is possible to change the environment and context around the decision maker and it is necessary to adapt the selected case. Third, if the selected case is not available or the decision maker doesn't satisfy according to the newly arrived context, then constraint satisfaction problem and solution ontology is applied to derive new solution for the decision maker. The constraint satisfaction problem uses to the previously selected case to adopt and solution ontology. The verification of the proposed methodology is processed by searching a meeting place according to the decision maker's requirements and context, the extracted solution shows the satisfaction depending on meeting purpose.

• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.3
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• pp.109-121
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• 2004

This paper presents an optimal design method for structure-borne durability of a vehicle body structure. Structure-borne durability design requires a new design that can increase fatigue lives of critical areas in a structure and must prohibit transition phenomenon of critical areas that results from modification of the structure at the same time. Therefore, the optimization problem fur structure-borne durability design are consists of an objective function and design constraints of 2 types; type 1-constraint that increases fatigue lives of the critical areas to the required design limits and type 2-constraint that prohibits transition phenomenon of critical areas. The durability design problem is generally dynamic because a designer must consider the dynamic behavior such as fatigue analyses according to the structure modification during the optimal design process. This design scheme, however, requires such high computational cost that the design method cannot be applicable. For the purpose of efficiency of the durability design, we presents a method which carry out the equivalent static design problem instead of the dynamic one. In the proposed method, dynamic design constraints for fatigue life, are replaced to the equivalent static design constraints for stress/strain coefficients. The equivalent static design constraints are computed from static or eigen-value analyses. We carry out an optimal design for structure-borne durability of the newly developed bus and verify the effectiveness of the proposed method by examination of the result.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.1
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• pp.77-85
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• 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.

• Journal of Mechanical Science and Technology
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• v.18 no.1
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• pp.122-131
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• 2004

A constraint equation-based control law design for large angle attitude maneuvers of flexible spacecraft is addressed in this paper The tip displacement of the flexible spacecraft model is prescribed in the form of a constraint equation. The controller design is attempted in the way that the constraint equation is satisfied throughout the maneuver. The constraint equation leads to a two-point boundary value problem which needs backward and forward solution techniques to satisfy terminal constraints. An observer-based tracking control law takes the constraint equation as the input to the dynamic observer. The observer state is used in conjunction with the state feedback control law to have the actual system follow the observer dynamics. The observer-based tracking control law eventually turns into a stabilized system with inherent nature of robustness and disturbance rejection in LQR type control laws.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.188-188
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• 2000

The most important problem in target tracking can be said to be modeling the tracking system correctly. Although the simple linear dynamic equation for this model has used until now, the satisfactory performance could not be obtained owing to uncertainties of the real systems in the case of designing the filters baged on the dynamic equations. In this paper, we propose the extended robust Kalman filter (ERKF) which can be applied to the real target tracking system with the parameter uncertainties. A nonlinear dynamic equation with parameter uncertainties is used to express the uncertain system model mathematically, and a measurement equation is represented by a nonlinear equation to show data from the radar in a Cartesian coordinate frame. To solve the robust nonlinear filtering problem, we derive the extended robust Kalman filter equation using the Krein space approach and sum quadratic constraint. We show the proposed filter has better performance than the existing extended Kalman filter (EKF) via 3-dimensional target tracking example.

• Transactions of the Korean Society of Automotive Engineers
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• v.5 no.1
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• pp.154-161
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• 1997

This paper presents the method to eliminate the constraint reaction in the Lagrange multiplier form equation of motion by using a generalized coordinate driveder from the velocity constraint equation. This method introduces a matrix method by considering the m dimensional space spanned by the rows of the constraint jacobian matrix. The orthogonal vectors defining the constraint manifold are projected to null vectors by the tangential vectors defined on the constraint manifold. Therefore the orthogonal projection matrix is defined by the tangential vectors. For correcting the generalized position coordinate, the optimization problem is formulated. And this correction process is analyzed by the quasi Newton method. Finally this method is verified through 3 dimensional vehicle model.

• Elastomers and Composites
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• v.34 no.4
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• pp.321-331
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• 1999

The curing process is the final step in tire manufacturing whereby a green tire built from layers of rubber compounds is formed to the desired shape and the compounds are converted to a strong, elastic materials to meet tire performance needs under elevated pressure and temperature in a press. A numerical optimization procedure was developed to improve product quality in a tire curing process. First, a dynamic constrained optimization problem was formulated to determine the optimal condition of the supplied cure media during a curing process. The objective function is subject to an equality constraint representing the process model that describes the heat transfer and cures kinetic phenomena in a cure press and is subject to inequality constraints representing temperature limits imposed on cure media. Then, the optimization problem was solved to determine optimal condition of the supplied cure media for a tire using the complex algorithm along with a finite element model solver.

• Journal of KIISE:Computer Systems and Theory
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• v.26 no.10
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• pp.1264-1274
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• 1999

본 논문에서는 분산된 클록들을 주기적으로 동기화 시키는 분산 실시간 시스템에서 시간적 제약을 만족시키기 위한 정적/동적 시간 제약(timing constraint) 변환 기법을 제안한다. 전형적인 이산클록동기화(discrete clock synchronization) 알고리즘은 클록의 값을 순간적으로 조정하여 클록의 시간이 불연속적으로 진행한다. 이러한 시간상의 불연속성은 시간적 이벤트를 잃어버리거나 다시 발생시키는 오류를 범하게 한다.클록 시간의 불연속성을 피하기 위해 일반적으로 연속클록동기화(continuous clock synchronization) 기법이 제안되고 있지만 소프트웨어적으로 구현되면 많은 오버헤드를 유발시키는 문제점이 있다. 본 논문에서는 시간적 제약을 동적으로 변환시키는 DCT (Dynamic Constraint Transformation) 기법을 제안하였으며, 이를 통해 기존의 이산클록동기화 알고리즘을 수정하지 않고서도 클록 시간의 불연속성에 의한 문제점들을 해결할 수 있도록 하였다. 아울러 DCT에 의해 이산클록동기화 하에서 생성된 태스크 스케쥴이 연속클록동기화에 의해 생성된 스케쥴과 동일함을 증명하여 DCT의 동작이 이론적으로 정확함을 증명하였다.또한 분산 실시간 시스템에서 지역 클록(local clock)이 기준 클록과 완벽하게 일치하지 않아서 발생하는 스케쥴링상의 문제점을 다루었다. 이를 위해 먼저 두 가지의 스케쥴링 가능성, 지역적 스케쥴링 가능성(local schedulability)과 전역적 스케쥴링 가능성(global schedulability)을 정의하고, 이를 위해 시간적 제약을 정적으로 변환시키는 SCT (Static Constraint Transformation) 기법을 제안하였다. SCT를 통해 지역적으로 스케쥴링 가능한 태스크는 전역적으로 스케쥴링이 가능하므로, 단지 지역적 스케쥴링 가능성만을 검사하면 스케쥴링 문제를 해결할 수 있도록 하였고 이를 수학적으로 증명하였다.Abstract In this paper, we present static and dynamic constraint transformation techniques for ensuring timing requirements in a distributed real-time system possessing periodically synchronized distributed local clocks. Traditional discrete clock synchronization algorithms that adjust local clocks instantaneously yield time discontinuities. Such time discontinuities lead to the loss or the gain of events, thus raising serious run-time faults.While continuous clock synchronization is generally suggested to avoid the time discontinuity problem, it incurs too much run-time overhead to be implemented in software. We propose a dynamic constraint transformation (DCT) technique which can solve the problem without modifying discrete clock synchronization algorithms. We formally prove the correctness of the DCT by showing that the DCT with discrete clock synchronization generates the same task schedule as the continuous clock synchronization.We also investigate schedulability problems that arise when imperfect local clocks are used in distributed real-time systems. We first define two notions of schedulability, global schedulability and local schedulability, and then present a static constraint transformation (SCT) technique. The SCT ensures that it is sufficient to check the schedulability of a task locally in a node with a local clock, since the global schedulability of the task is derived from its local schedulability through SCT. We formally prove the correctness of SCT.