• Journal of Intelligence and Information Systems
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• v.6 no.2
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• pp.29-40
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• 2000

Process planning (selection and ordering of processes) and material selection for product manufacturing are two key things determined before taking full-scale manufacturing. Knowledge on product design. material characteristics, processes, time and cost all-together are mutually related and should be considered concurrently. Due to the complexity of problem, human experts have got only one of the feasilbe solutions with their field knowledge and experiences. We propose a hierarchical expert system framework of knowledge representation and reasoning in order to overcome the complexity. Manufacturing processes have inherently hierarchical relationships, from top level processes to bottom level operation processes. Process plan of one level is posted in process blackboard and used for lower level process planning. Process information on blackboard is also used to adjust the process plan in order to resolve the dead-end or inconsistency situation during reasoning. Decision variables for process, material, tool, time and cost are represented as object frames, and their relationships are represented as constraints and rules. Constraints are for relationship among variables such as compatibility, numerical inequality etc. Rules are for causal relationships among variables to reflect human expert\`s knowledge such as process precedence. CRSP(Constraint and Rule Satisfaction Problem) approach is adopted in order to obtain solution to satisfy both constraints and rules. The trade-off procedure gives user chances to see the impact of change of important variables such as material, cost, time and helps to determine the preferred solution. We developed the prototype system using visual C++ MFC, UNIK, and UNlK-CRSP on PC.

• Journal of Intelligence and Information Systems
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• v.6 no.1
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• pp.83-96
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• 2000

본연구는 웹 상에서 원격 협력 학습을 위한 수준별 협력 학습자 진단 및 스케줄링 에이전트의 설계와 구현에 관한 연구이다. 원격 협력 학습은 동일한 학습내용에 흥미를 갖는 아동이 동시에 학습할 수 있는 환경이 필요하며 학습자의 지식 또한 비슷한 수준이어야 효과적인 협력학습을 할 수 있다. 분산 환경의 이질적인 학습자를 모으기 위해서는 좀 더 자율적이고 지능적인 시스템이 필요하며 학습자에 대한 지식을 표현하는 학습자 모델이 요구된다. 이를 위해 에이전트 시스템이 적절하게 사용될수 있으며 학습자의 수준을 판단하기 위한 진단 에이전트와 협력학습이 가능한 여러명의 학습자들을 알맞은 시간과 서버에 연결하는 스케줄링 에이전트를 웹 기반 지능형 교수 시스템에 접목하였다. 학습자 수준을 진단하는 진단 에이전트는 확신도를 높이기 위해 3-모수 로지스틱 확신공식과 시간 가중치 확신인자 공식을 적용하여 신뢰도를 높였다 또한 협력학습의 스케줄링을 위해 다양한 제약조건들의 최적해를 구하기 위해 제약 만족 문제(CSP)로 스케줄링 에이전트를 모델링하였다 본 연구에서 설계 구현한 협력학습자 진단 및 스케줄링 에이전트의 효율성을 살펴보기 위해 여러명의 학습자를 대상으로 실험하였다. 실험을 통해 각 학습자의 지식 수준 진단과 다수의 학습자가 적절한 협력학습을 하기 위한 스케줄링이 매우 효율적으로 이루어짐을 볼 수 있었다.

• The Journal of Society for e-Business Studies
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• v.17 no.4
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• pp.141-153
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• 2012

According to the environment change of market, supply chain network needs to be redesigned for efficient provision of product within the budget constraint. Also, it is desired that the customer satisfaction such as on time delivery should be considered as an important element at redesigning of supply chain network in addition to the cost reduction. In this paper redesign of supply chain network for its expansion is treated as a problem situation and a related mathematical model is suggested. Moreover, the numerical examples about the total weighted distance of the redesigned supply chain network are presented with various budget constraints by using genetic algorithm to help the managerial decision.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.32 no.1
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• pp.29-34
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• 2008

The efforts of reflecting the system's uncertainties in design step have been made and robust optimization or reliability-based design optimization are examples of the most famous methodologies. In their formulation, the mean and standard deviation of a performance function and constraints expressed by probability conditions are involved. Therefore, it is essential to effectively and accurately calculate them and, in addition, the sensitivity results are required to obtain when the nonlinear programming is utilized during optimization process. We aim to obtain the new and efficient sensitivity formulation, which is based on integral form, on statistical moments such as the mean and standard deviation, and probability constraints. It does not require the additional functional calculation when statistical moments and failure or satisfaction probabilities are already obtained at a design point. Moreover, some numerical examples have been calculated and compared with the exact solution or the results of Monte Carlo Simulation method. The results seem to be very satisfactory.

• Journal of Korean Institute of Industrial Engineers
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• v.24 no.4
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• pp.649-660
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• 1998

Steel making in Mini Mill consists of three major processing stages: molten steel making in an electric arc fuenace, slab casting in a continuous caster, and hot rolling in a finishing mill. Each processing stage has its own lot grouping criterion. However, these criteria in three stages are conflicting with each other. Therefore, delveloping on efficient lot grouping algorithm to enhance the overall productivity of the Mini Mill is an extremely difficult task. The algorithm proposed in this paper is divided into three steps hierarchically: change grouping, cast grouping, and roll grouping. An efficient charge grouping heuristic is developed by exploiting the characteristics of the orders, the processing constraints and the requirements for the downstream stages. In order to maximaize the productivity of the continuous casters, each cast must contain as many charges as possible. Based on the constraint satisfaction problem technique, an efficient cast grouping heuristic is developed. Each roll consists of two casts satisfying the constraints for rolling. The roll grouping problem is formulated as a weighted non-bipartite matching problem, and an optimal roll grouping algorithm is developed. The proposed algorithm is programmed with C language and tested on a SUN Workstation with real data obtained from the H steel works. Through the computational experiment, the algorithm is verified to yield quite satisfactory solutions within a few minutes.

• Proceedings of the Korea Information Processing Society Conference
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• 2002.11a
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• pp.389-392
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• 2002

본 논문에서는 대표적인 NP 문제의 하나인 강의시간표 문제를 분산 제약조건 만족 문제로 해결하는 시스템을 제안한다. 제안한 시스템에서는 복잡하고 방대한 강의시간표 문제를 여러 개의 작은 모듈 단위의 에이전트로 분할한 후 개별 문제외 해를 구하고 이들을 결합시켜 가능해(feasible solution)를 찾는다. 한편, 분리된 에이전트에 의해 해결되는 부-문제들이 상호 의존적이면서 중첩된 경우에 해들 사이의 모순을 해결하면서 최종 해를 구한다. 제안한 시스템에서는 다음과 같은 방법으로 문제를 해결한다. 제약조건을 점진적으로 추가하여 탐색공간을 줄여 나간 후, 국소 탐색을 통해 변수에 일관된 도메인 값을 할당한다. nogood에 대하여 점진적인 제약조건 완화로 탐색공간을 확장하여 모든 변수에 도메인 값을 배정한다. 제약조건 완화는 제약조건들을 몇몇 단계로 정의하고, 휴리스틱 순서와 제약조건의 중요도에 따라 되추적 탐색 기법을 이용하여 순차적으로 완화한다. 만일 과잉-제약조건이 발생할 경우 가중치의 합이 최소로 하는 값을 배정한다. 즉 모든 변수에 도메인 값은 모든 제약조건을 만족하든 초기의 부-문제에 가능해가 될 수 있는 제약조건을 만족해야 한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.10
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• pp.4848-4863
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• 2016

The explosive wireless data service requirement accompanied with carbon dioxide emission and consumption of traditional energy has put pressure on both industria and academia. Wireless networks powered with the uneven and intermittent generated renewable energy have been widely researched and lead to a new research paradigm called green communication. In this paper, we comprehensively consider the total generated renewable energy, QoS requirement and channel quality, then propose a utility based renewable energy allocation policy. The utility here means the satisfaction degree of users with a certain amount allocated renewable energy. The energy allocation problem is formulated as a constraint optimization problem and a heuristic algorithm with low complexity is derived to solve the raised problem. Numerical results show that the renewable energy allocation policy is applicable not only to soft QoS, but also to hard QoS and best effort QoS. When the renewable energy is very scarce, only users with good channel quality can achieve allocated energy.

• Journal of the Korean Institute of Gas
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• v.8 no.2 s.23
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• pp.28-34
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• 2004

Enhanced methodologies for process diagnosis and abnormal situation management have been developed for the last two decades. However, there is no single method that always shows better performance over all kinds of diagnostic problems. In this paper, a framework of message-passing, cooperative, intelligent diagnostic agents is presented for improved on-line fault diagnosis through cooperative problem solving of different expertise. A group of diagnostic agents in charge of different process functional perform local diagnoses in parallel; exchange related information with other diagnostic agents; and cooperatively solve the global diagnostic problem of the whole process plant or business units just like human experts would do. For their better understanding, sharing and exchanging of process knowledge and information, we also suggest a way of remodeling processes and protocols, taking into account semantic abstracts of process information and data. The benefits of the suggested multi-agents-based approach are demonstrated by the implementations for solving the diagnostic problems of various chemical processes.

• Journal of Aerospace System Engineering
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• v.15 no.5
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• pp.8-15
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• 2021

This paper describes a design method using an optimization technique to satisfy the longitudinal handling quality of high maneuverable jet aircraft. The dynamic inversion technique was applied to the target aircraft, and the control gain optimization satisfied the longitudinal short-period handling quality, however, the stability margin was not considered. If the stability margin is not satisfied, it is necessary to directly readjust the gains through trial and error methods for improvement. To improve this, an additional compensator and an optimization constraint were added to the control gain optimization procedure. In addition, the degree of handling quality satisfaction with the optimization result was reevaluated, and additional control evaluation criteria for the convergence of the time response and the steady state error that the flight performance requirement set as the optimization constraint cannot be reflected, and the results are described.

• Journal of Information Technology Services
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• v.11 no.2
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• pp.19-47
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• 2012

Contemporary smartphone competition is generally described as the battle between Apple's proprietary platform and Google's open platform. However, this competition is not limited within smartphone adoption itself. User's pre-adoption of one mobile platform via smartphone can be connected to the post-adoption of the same mobile platform based on the other smart devices (e.g. smart pad). In this study, we investigate whether user's preference to a certain platform is persistent over mobile ecology, from the pre-adoption of one smart device to the post-adoption of following devices. For this investigation, we adopt the dual-model as the ground theory, where post-adoption of IT product is explained by both dedication and constraint factors. The empirical testing first evidences that dual model works well as our research model for identifying the reasons of post-adoption. Next, we group our data into two parts in order to compare the switching behavior of iPhone users and Android phone users. iPhone users show much lower switching rate to Android based smart pads, while Android phone users show higher churn rate to iPad (49.3% : 96.3%). Especially, satisfaction showed much stronger effect than switching cost on the continuing intention of existing platform, when the analysis is given to the iPhone user's group. From this result, we can conjecture the relatively stronger loyalty of iPhone users. More managerial implications on the mobile platform strategy are driven.