• ETRI Journal
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• 제37권5호
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• pp.888-897
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• 2015

Group scheduling is an operation whereby control packets arriving in a time slot schedule their bursts simultaneously. Normally, those bursts that are of the same wavelength are scheduled on the same channel. In cases where the support of full wavelength converters is available, such scheduling can be performed on multiple channels for those bursts that are of an arbitrary wavelength. This paper presents a new algorithm for group scheduling on multiple channels. In our approach, to reach a near-optimal schedule, a maximum-weight clique needs to be determined; thus, we propose an additional algorithm for this purpose. Analysis and simulation results indicate that an optimal schedule is almost attainable, while the complexity of computation and that of implementation are reduced.

• 산업경영시스템학회지
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• 제18권34호
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• pp.99-106
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• 1995

Recently, neural network is recognized as a new approach to solve jobshop scheduling problems in manufacturing system. Scheduling problem is known to be a difficult combinational explosive problem with domain-dependence variations in general. In addition, the needs to achieve a good performance in flexible manufacturing system increase the dimensions of decision complexity. Therefore, mathematical approach to solve realistic problems could be failed to find optimal or optimal-trending. In this paper a technique with neural network for jobs grouping by job-attributes and Gaussian machine network for generating to near-optimal sequence is presented.

• 제어로봇시스템학회논문지
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• 제4권2호
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• pp.235-245
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• 1998

This paper presents the fuzzy optimization model based scheduling methodology for the efficient production control of a FFS(FIexible Flow Shop) under the uncertain production environment. To develop the methodology, a fuzzy optimization technique is introduced in which the uncertain production capacity caused by the random events like the machine breakdowns or the absence of workers is modeled by fuzzy number. Since the problem is NP hard, the goal of this study is to obtain the near optimal but practical schedule in an efficient way. Thus, Lagrangian relaxation method is used to decompose the problem into a set of subproblems which are easier to solve than the original one. Also, to construct the feasible schedule, a heuristic algorithm was proposed. To evaluate the performance of the proposed method, computational experiments, based on the real factory data, are performed. Then, the results are compared with those of the other methods, the deterministic one and the existing one used in the factory, in the various performance indices. The comparison results demonstrate that the proposed method is more effective than the other methods.

• 전자공학회논문지A
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• 제29A권4호
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• pp.74-82
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• 1992

This paper deals with the scheduling problems, which are the most important subtask in High-level Synthesis. ILP(integer linear programming) formulations are used as a scheduling problem approach.For practical application to digital system design, we have concentrated our attentions on pipelined datapath scheduling. For experiment results, we choose the 5-th order digital wave filter as a benchmark and do the schedule. Finally, we can obtain better and near-optimal scheduling results.

• 대한기계학회논문집A
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• 제21권5호
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• pp.769-779
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• 1997

This paper presents an approach to multiple objective scheduling of flexible manufacturing systems(FMS). The approach is an extension of the scheduling method that formulates scheduling problems using Petrinets, and applies heuristic search to find optimal or near-optimal schedules with a single objective. New evaluation functions are developed to optimize simultaneously the makespan and the total operating cost. A scheduling example is used to demonstrate the effectiveness of the proposed approach.

• 대한기계학회논문집A
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• 제25권3호
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• pp.443-451
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• 2001

This paper addresses an on-line scheduling method for track systems in semiconductor fabrication. A track system is a clustered equipment performing photolithography process in semiconductor fabrication. Trends toward high automation and flexibility in the track systems accelerate the necessity of the intelligent controller that can guarantee reliability and optimize productivity of the track systems. This paper proposes an-efficient on-line scheduling method that can avoid deadlock inherent to track systems and optimize the productivity. We employ two procedures for the on-line scheduling. First, we define potential deadlock set to apply deadlock avoidance policy efficiently. After introducing the potential deadlock set, we propose a deadlock avoidance policy using an on-line Gantt chart, which can generate optimal near-optimal schedule without deadlock. The proposed on-line scheduling method is shown to be efficient in handling deadlock inherent to the track systems through simulation.

• 한국건설관리학회논문집
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• 제8권6호
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• pp.235-245
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• 2007

This research study presents the development and application of an Elitist Genetic Algorithm (Elitist GA) for solving the resource-constrained project scheduling problem, which is one of the most challenging problems in construction engineering. Main features of the developed algorithm are that the elitist roulette selection operator is developed to preserve the best individual solution for the next generation so as to obtain the improved solution, and that parallel schedule generation scheme is used to generate a feasible solution to the problem. The experimental results on standard problem sets indicate that the proposed algorithm not only produces reasonably good solutions to the problems over the heuristic method and other GA, but also can find the optimal and/or near optimal solutions for the large-sized problems with multiple resources within a reasonable amount of time that will be applicable to the construction industry. This paper will help researchers and/or practitioners in the construction project scheduling software area with alternative means to find the optimal schedules by utilizing the advantages of the Elitist GA.

• 산업경영시스템학회지
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• 제23권56호
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• pp.9-18
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• 2000

This paper considers the problem of two-machine, M-parallel flow shop scheduling to minimize makespan, and proposes a series of heuristic algorithms and a branch and bound algorithm. Two processing times of each job at two machines on each line are identical on any line. Since each flow-shop line consists of two machines, Johnson's sequence is optimal for each flow-shop line. Heuristic algorithms are developed in this paper by combining a "list scheduling" method and a "local search with global evaluation" method. Numerical experiments show that the proposed heuristics can efficiently give optimal or near-optimal schedules with high accuracy. with high accuracy.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2005년도 추계종합학술대회
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• pp.1213-1216
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• 2005

In this paper, we suggested the integer linear programming (ILP) models that went through constraint scheduling to simple cycle operation during the delay time. The delayed scheduling can determine a schedule with a near-optimal number of control steps for given fixed hardware constraints. In this paper, the resource-constrained problem is addressed, for the DFG optimization for multiprocessor design problem, formulating ILP solution available to provide optimal solution. The results show that the scheduling method is able to find good quality schedules in reasonable time.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 22-24 Oct. 1991
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• pp.1718-1723
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• 1991

The determination of a production sequence is an important problem in a batch process operation. In this paper a new algorithm for a near optimal production sequence of N product in an M unit serial multiproduct batch process is proposed. The basic principle is the same as that of Johnson's algorithm for two-unit UIS system. Test results on a number of selected examples exhibit the superiority over previously reported results. In addition, a tabulation technique is presented to calculate the makespan of a given sequence of production for all processing units under UIS mode.