• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.517-520
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• 2003

A quasi-optimization algorithm for generating a chain restaurant work scheduling (WS) is proposed based on Genetic Algorithm with fuzzy logic, where the whole weekly chain restaurant WS problem is decomposed to 7 daily WS problems and a combined weekly WS problem. Experimental result shows that a weekly schedule for 15 workers and 24 hours in a chain restaurant is produced in 6 minutes using the proposed algorithm implemented with C++ and executed on a PC(Athlon XP 1900+), where the quality of WS is satisfactorily evaluated by professional experts.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.10a
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• pp.173-176
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• 2004

유비쿼터스 컴퓨팅 환경에서는 각 클라이언트는 자신이 처한 환경에 따라서 여러 가지 장치를 사용할 수 있고, 각 장치는 각기 다른 클라이언트의 요구를 동시에 받을 수 있다. 본 논문에서는 클라이언트들이 보내는 프린트 요청을 받아 사용자에게 적절한 프린터로 출력하는 유비쿼터스 컴퓨팅 환경에서의 프린터 서버를 가정한다. 그러나 프린터 서버는 많은 클라이언트로부터 동시에 프린트 요청을 받을 수 있으므로, 가능한 모든 클라이언트의 요청을 만족시킬 수 있는 스케줄링을 해야 한다. 이러한 목적을 위한 유전자알고리즘을 이용한 유비쿼터스 환경에서의 실시간 프린터 스케줄링 방법을 제안한다.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.1
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• pp.69-74
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• 2004

A sequencing problem is to find an ordered sequence of some entities which maximizes (or minimize) the domain specific objective function. As some typical examples of sequencing problems, there are traveling salesman problem, job shop scheduling, flow shop scheduling, and so on. This paper introduces a new type of sequencing problems, named a sequencing problem with fuzzy preference relation, where a fuzzy preference relation is provided for the evaluation of the quality of sequences. It presents how such a problem can be formulated in terms of objective function. It also proposes a genetic algorithm applicable to such a sequencing problem.

• International conference on construction engineering and project management
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• 2005.10a
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• pp.366-370
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• 2005

The construction environment is dynamic in nature and is characterized by various degrees of uncertainties. The uncertainties such as lack of coordination, non availability of resources, condition of temporary structures and varying weather conditions have a significant impact on estimating the duration of activities. These are subjective, vague and imprecisely defined and are expressed in subjective measures rather than mathematical terms. Conventionally, various quantitative techniques such as CPM and PERT have emerged in construction industry. These techniques cannot solve the above problems and rely on human experts which may not always be possible. In such situations Artificial Intelligence tools such as fuzzy sets and neural networks handle such variables and provide global strategies. The present paper evaluates the effect of qualitative factors to identify the activity duration using new intelligent approach. The results are compared with conventional methods for effective project management. A case study is considered to demonstrate the applicability of fuzzy logic for project scheduling.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1993.04a
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• pp.119-119
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• 1993

• 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.

• Journal of Intelligence and Information Systems
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• v.13 no.3
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• pp.63-82
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• 2007

In this paper, we propose an adaptive hybrid genetic algorithm (ahGA) approach for effectively solving multistage-based scheduling problems in flexible manufacturing system (FMS) environment. The proposed ahGA uses a neighborhood search technique for local search and an adaptive scheme for regulation of GA parameters in order to improve the solution of FMS scheduling problem and to enhance the performance of genetic search process, respectively. In numerical experiment, we present two types of multistage-based scheduling problems to compare the performances of the proposed ahGA with conventional competing algorithms. Experimental results show that the proposed ahGA outperforms the conventional algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.11
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• pp.5243-5263
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• 2017

Data center networks provide critical bandwidth for the continuous growth of cloud computing, multimedia storage, data analysis and other businesses. The problem of low link bandwidth utilization in data center network is gradually addressed in more hot fields. However, the current scheduling strategies applied in data center network do not adapt to the real-time dynamic change of the traffic in the network. Thus, they fail to distribute resources due to the lack of intelligent management. In this paper, we present an improved adaptive traffic scheduling strategy utilizing the simulated annealing genetic algorithm (SAGA). Inspired by the idea of software defined network, when a flow arrives, our strategy changes the bandwidth demand dynamically to filter out the flow. Then, SAGA distributes the path for the flow by considering the scheduling of the different pods as well as the same pod. It is implemented through software defined network technology. Simulation results show that the bisection bandwidth of our strategy is higher than state-of-the-art mechanisms.

• Journal of Intelligence and Information Systems
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• v.13 no.4
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• pp.121-135
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• 2007

Constraint directed scheduling techniques, representing problem constraints explicitly and constructing schedules by constrained heuristic search, have been successfully applied to real world scheduling problems that require satisfying a wide variety of constraints. However, there has been little basic research on the representation and optimization of the objective value of a schedule in the constraint directed scheduling literature. In particular, the cost objective is very crucial for enterprise decision making to analyze the effects of alternative business plans not only from operational shop floor scheduling but also through strategic resource planning. This paper aims to explicitly represent and optimize the total cost of a schedule including the tardiness and inventory costs while satisfying non-relaxable constraints such as resource capacity and temporal constraints. Within the cost based scheduling framework, a cost propagation algorithm is presented to update cost information throughout temporal constraints within the same job.

• Korean Management Science Review
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• v.12 no.2
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• pp.43-62
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• 1995

For a complex scheduling system like time table construction, its optimal solution, if exists, is hard to obtain. In this paper, the scheduling environment is reasonably confined as where objects have their own events competing for better slots on boards, and objects have their own board slot preferences and belong to one or more classes of the society which globally constrains them. Here, two phase method is suggested, where the first phase is human-like preference driven and the second phase is for fine tuning by considering all the factors given. Designed and implemented in our system HI-SCHED are dynamic object switching, temporal-constraint-driven intelligent backtracking, case-based revisions, object-based approach, and so on. Some satisfaction degrees are also defined to measure the usefulness of our method. In addition, look-ahead dynamic object switching is considered, and additional global constraints are introduced and processed. A simple scheme is also used to verify the usefulness of the post processing scheme.