• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.286-289
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• 1989

The purpose of this paper is to design a job scheduling algorithm utilizing intelligent control technique. Rulebase is built through the evaluation of rule-set scheduling. 24 scheduling rule-sets and meta-rules are employed. An appropriate scheduling rule-set is selected based on this rulebase and current manufacturing system status. Six criteria have been used to evaluate the performance of scheduling. The performance of sheduling is dependent on random breakdown of the major FMS components during simulation.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2009.06a
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• pp.1057-1058
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• 2009

• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1564-1569
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• 1991

In this paper we describe Flexible Manufacturing Systems (FMS) using Petri nets, since Petri nets provide a powerful tool for modeling dynamical behavior of discrete concurrent processes. We deal with off-Line and on-Line rule-based scheduling of FMS. The role of the rule-base is to generate appropriate priority rule for resolving conflicts, that is, for selecting one of enabled transitions to be fired in a conflict set of the Petri nets. This corresponds to select a part type to be processed in the FMS. Towards developing more Intelligent Manufacturing Systems (IMS) we propose a conceptual framework of a futuristic intelligent scheduling system.

• Journal of the Korean Operations Research and Management Science Society
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• v.27 no.2
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• pp.97-109
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• 2002

Manufacturing environments in the real world are subject to many sources of change and uncertainty, such as new job releases, job cancellations, a chance in the processing time or start time of some operation. Thus, the realistic scheduling method should Properly reflect these dynamic environment. Based on the release times of jobs, JSSP (Job Shoe Scheduling Problem) can be classified as static and dynamic scheduling problem. In this research, we mainly consider the dynamic JSSP with continually arriving jobs. The goal of this research is to develop an efficient scheduling method based on GA (Genetic Algorithm) to address dynamic JSSP. we designed scheduling method based on SGA (Sing1e Genetic Algorithm) and PGA (Parallel Genetic Algorithm) The scheduling method based on GA is extended to address dynamic JSSP. Then, This algorithms are tested for scheduling and rescheduling in dynamic JSSP. The results is compared with dispatching rule. In comparison to dispatching rule, the GA approach produces better scheduling performance.

• Journal of the Korea Institute of Military Science and Technology
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• v.15 no.3
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• pp.322-333
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• 2012

AESA radar is able to instantaneously and adaptively position and control the beam, and such adaptive beam pointing of AESA radar enables to remarkably improve the multi-mission capability. For this reason, Radar Resource Management(RRM) becomes new challenging issue. RRM is a technique efficiently allocating finite resources, such as energy and time to each task in an optimal and intelligent way. Especially radar beam scheduling is the most critical component for the success of RRM. In this paper, we proposed a rule-based scheduling algorithm and Simulated Annealing(SA) based scheduling algorithm, which are alternatively selected and applied to beam scheduler according radar load status in real-time. The performance of the proposed algorithm was evaluated on the multi-function radar scenario. As a result, we showed that our proposed algorithm can process a lot of beams at the right time with real time capability, compared with applying only rule-based scheduling algorithm. Additionally, we showed that the proposed algorithm can save scheduling time remarkably, compared with applying only SA-based scheduling algorithm.

• Journal of Korean Institute of Industrial Engineers
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• v.23 no.1
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• pp.197-213
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• 1997

It is not easy to find a good production schedule which can be used in practice. Therefore, production scheduling simulation with a simple dispatching rule or a set of dispatching rules is used. However, a simple dispatching rule may not create a robust schedule, for the same rule is blindly applied to all internal production processes. The presumption is that there might be a specific combination of appropriate rules that can improve the efficiency of a total production system for a certain type of orders. In order to acquire a better set of dispatching rules, simulation is used to examine the performance of various combinations of dispatching rule sets. There are innumerable combination of rule sets. Hence it takes too much computer simulation time to find a robust set of dispatching rule for a specific production system. Therefore, we propose a concept of the knowledge based simulation to circumvent the problem. The knowledge based simulation consists of knowledge bases, an inference engine and a simulator. The knowledge base is made of rule sets that is extracted from both simulation and human intuition obtained by the simulation studies. For a certain type of orders, the proposed system provides several sets of dispatching rules that are expected to generate better results. Then the scheduler tries to find the best by simulating all proposed set of rules with the simulator. The knowledge-based simulator armed with the acquired knowledge has produced improved solutions in terms of time and scheduling performance.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1992.04b
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• pp.249-257
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• 1992

An automated machining system involves concurrent use of manufacturing resources, alternative process plans, and flexible routings. High investment in the installation of automated facilities requires an efficient scheduling system that is able to allocate the resources specified for operations over a scheduling horizon. The primary emphasis of this paper is to generate schedules that accurately reflect details of the automated environment and the objectives stated for the system. In this paper, a scheduling algorithm for automated machining is presented. Using the previous simulation research for this topic, a rule-based scheduling system is constructed. An architecture for an intelligent scheduling system is proposed, and the system has a high potential to provide efficient schedules based on the task-specific knowledge for the dynamic scheduling environment

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.5
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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.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.41 no.8
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• pp.831-840
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• 1992

This paper presents an efficient short-term generation scheduling method using a rule-based expert/consulting system approach to assist electric energy system operators and planners. The expert system approach is applied to improve the Dynamic Programming(DP) based generation scheduling algorithm. In the selection procedure of the feasible combinations of generating units at each stage, automatic consulting on the manipulation of several constraints such as the minimum up time, the minimum down time and the maximum running time constraints of generating units will be performed by the expert/consulting system. In order to maximize the solution feasibility, the aforementioned constraints are controlled by a rule-based expert system, that is, instead of imposing penalty cost to those constraint violated combinations, which sometimes may become the very reason of no existing solution, several constraints will be manipulated within their flexibilities using the rules and facts that are established by domain experts. In this paper, for the purpose of implementing the consulting of several constraints during the dynamic process of generation scheduling, an expert system named STGSCS is developed. As a building tool of the expert system, C Language Integrated Production System(CLIPS) is used. The effectiveness of the proposed algorithm has been demonstrated by applying it to a model electric energy system.

• Korea Journal of Hospital Management
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• v.16 no.4
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• pp.161-182
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• 2011

In today's competitive dental markets, it is of paramount importance to improve service quality and at the same time to use scarce resource efficiently. In this study, we present appointment policies and scheduling rules for private dental clinics to reduce the waiting time of patients and to increase the revenue by utilizing resource more effectively. This study validates the proposed appointment policies and scheduling rules based on simulation models. We show that the bottleneck-based appointment policy is the most effective among appointment policies, followed by the multiple-block appointment one. The shortest processing time among scheduling rules contributes most to the performance of the appointment system.