• 대한전기학회논문지
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• 제39권5호
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• pp.527-537
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• 1990

This paper describes an intelligent control-based job scheduler, named ESIJOBS, for flexible manufacturing system. In order to construct rulebase of this system, traditional rules of job scheduling in FMS are examined and evaluated. This result and the repetitional simulations with graphic monitoring system are used to form the rulebase of ESIJOBS, which is composed of three parts:six part selection rules, four machine center selection rules, and twenty-one metarules. Appropriate scheduling rule sets are selected by this rulebase and manufacturing system status. The performances of all simulations are affected by random breakdowns of major FMS components during each simulation. Six criteria are used to evaluate the performance of each scheduling. The two modes of ESIJOBS are simulated and compared with combinational 24 rule-set simulations. In this comparison ESIJOBS dominated the other rule-set simulations and showed the most excellent performance particularly in three criteria.

• 경영과학
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• 제13권3호
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• pp.173-186
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• 1996

This paper presents an approach for classifying scheduling problems and selecting a heuristic rule to yield best solution in terms of certain performance measure(s). Classification parameters are employed from previous studies on job shop scheduling and project scheduling. Neural network is used for learning and estimating the performance of heuristic rules. In addition, multi-criteria decision making techniques are employed to combine the preferences for each performance measure and heuristic rule for the problems with multi-objectives.

• 경영과학
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• 제32권4호
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• pp.69-80
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• 2015

The semiconductor industry is one of those in which the most intricate processes are involved and there are many critical factors that are controlled with precision in those processes. Naturally production scheduling in the semiconductor industry is also very complex and studied by the industry and academia for many years; however, still there are many issues left unclear in the problem. This paper proposes an multi-objective optimization-based scheduling method for semiconductor fabrication(fab). Two main objectives are throughput maximization and meeting target production quantities. The first objective aims to reduce production cost, especially the fixed cost incurred by a large investment constructing a new fab facility. The other is meeting customer orders on time and also helps a fab maintain stable throughput through controlled WIP balancing in the long run. The paper shows a trade-off structure between the two objectives through experimental studies, which provides industrial practitioners with useful references.

• International Journal of Computer Science & Network Security
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• 제21권1호
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• pp.19-26
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• 2021

CPU is considered the main and most important resource in the computer system. The CPU scheduling is defined as a procedure that determines which process will enter the CPU to be executed, and another process will be waiting for its turn to be performed. CPU management scheduling algorithms are the major service in the operating systems that fulfill the maximum utilization of the CPU. This article aims to review the studies on the CPU scheduling algorithms towards comparing which is the best algorithm. After we conducted a review of the Round Robin, Shortest Job First, First Come First Served, and Priority algorithms, we found that several researchers have suggested various ways to improve CPU optimization criteria through different algorithms to improve the waiting time, response time, and turnaround time but there is no algorithm is better in all criteria.

• 한국통신학회논문지
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• 제27권9C호
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• pp.853-860
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• 2002

본 논문에서는 ATM 계층에서 GFR 서비스의 공정성 기준을 만족시키고, 효율적인 셀 서비스를 위한 버퍼관리 및 스케줄링 기법을 제안하였다. 시뮬레이션을 통한 성능 분석 결과 기존의 WRR 방식에서 만족하지 못하는 공평성 기준 2(MCR plus equal share)를 만족시킬 수 있었다. 또한 수율면에서도 제안된 알고리즘이 기존의 WRR보다 약 29% 향상되었고 공평성 지표에서는 WRR보다 제안된 알고리즘이 더 우수함을 확인할 수 있었다.

• 대한전기학회논문지:전력기술부문A
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• 제54권7호
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• pp.352-357
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• 2005

In competitive electricity markets, the System Operator (SO) coordinates the overall maintenance schedules when the collective maintenance schedule reported to 50 by Gencos not satisfy the specified operating criteria, such as system reliability or supply adequacy. This paper presented a method that divides generator maintenance scheduling of the 50 into a master-problem and a sub-problem. Master-problem is schedule coordination and sub-problem is DC-optimal power flow. If sub-problem is infeasible, we use the algorithm of modifying operating criteria of master-problem. And, the 50 should use the open information only, because the information such as cost function of a generator and bidding Price is highly crucial for the strategies of profit maximization.

• International Journal of Computer Science & Network Security
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• 제21권3호
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• pp.304-310
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• 2021

The paper presents problems of optimization of the synthesis of embedded systems, in particular Pareto optimization. The model of such a system for its design for high-level of abstract is based on the classic approach known from the theory of task scheduling, but it is significantly extended, among others, by the characteristics of tasks and resources as well as additional criteria of optimal system in scope structure and operation. The metaheuristic algorithm operating according to this model introduces a new approach to system synthesis, in which parallelism of task scheduling and resources partition is applied. An algorithm based on a genetic approach with simulated annealing and Boltzmann tournaments, avoids local minima and generates optimized solutions. Such a synthesis is based on the implementation of task scheduling, resources identification and partition, allocation of tasks and resources and ultimately on the optimization of the designed system in accordance with the optimization criteria regarding cost of implementation, execution speed of processes and energy consumption by the system during operation. This paper presents examples and results for multi-criteria optimization, based on calculations for specifying non-dominated solutions and indicating a subset of Pareto solutions in the space of all solutions.

• 산업경영시스템학회지
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• 제33권4호
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• pp.153-158
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• 2010

This study presents a single machine scheduling algorithm to minimize total cost(lateness cost, earliness cost and failure cost) by controlling machining speed. Generally, production scheduling uses the information of process planning and machining speed is not changed at production scheduling. And failure cost is not consider for scheduling algorithm. Therefore, the purpose of this study is to consider the change of machining speed for efficient production scheduling. And performance criteria for algorithm considers total cost. Especially, failure cost of product by increasing machining speed is considered.

• 산업경영시스템학회지
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• 제21권47호
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• pp.35-45
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• 1998

Scheduling problem in Flexible Manufacturing Systems(FMS) is complex because of various situation of Manufacturing Systems. Especially, in case of short-term scheduling demanding high efficiency, low cost at short-period, efficient scheduling is a serious problem. To solve this problem, many dispatching rules are developed. But, it leave much to be desired, because real situation in shop floor is complex and real-time scheduling is needed in real manufacturing shop floor. In this paper, search algorithm that allocate different dispatching rules to each machine is presented to complement lack of dispatching rule and develop practical real-time scheduling system. The search algorithm is described in detail. First, algorithm detect machine breakdown, evaluate each dispatching rule. dispatching rules for each machine meeting performance criteria are ranked. The algorithm selects new dispatching nile for bottleneck machine. The effectivenes and efficiency of the mixed dispatching rule and search algorithm is demonstrated.

• Journal of information and communication convergence engineering
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• 제11권4호
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• pp.235-240
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• 2013

Cloud systems are popular computing environment because they can provide easy access to computing resources for users as well as efficient use of resources for companies. The resources of cloud computing are heterogeneous and jobs have various characteristics. One such issue is effective job scheduling. Scheduling in the cloud system may be defined as a multiple criteria decision model. To address this issue, this paper proposes a priority-based two-step job scheduling algorithm. On the first level, jobs are classified based on preference. Resources are dedicated to a job if a deadline failure would cause severe results or critical business losses. In case of only minor discomfort or slight functional impairment, the job is scheduled using a best effort approach. On the second level, jobs are allocated to adequate resources through their priorities that are calculated by the analytic hierarchic process model. We then analyze the proposed algorithm and make a scheduling example to confirm its efficiency.