• Journal of Korean Society of Industrial and Systems Engineering
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• v.14 no.24
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• pp.53-69
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• 1991

This paper is concerned with software developments for scheduling and sequencing of FMS. The scheduling algorithms are developed for 3 types of FMS:single machine type FMS, flowshop type FMS. assembly line type FMS. For the single machine type FMS. full enumeration algorithm is used. For the flowshop type FMS heuristic algorithms are developed. For the assembly type FMS the exsisting PERT/CPM algorithm is applied. Numerical examples are presented for illustration of each algorithm. Each soft ware program list are attached as appendices.

• Journal of Intelligence and Information Systems
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• v.2 no.2
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• pp.69-83
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• 1996

The objective of this research is to develop a knowledge acquisition and refinement method for a multi-objective and multi-decision FMS scheduling problem. A competitive neural network and an inductive learning algorithm are integrated to extract and refine necessary scheduling knowledge from simulation outputs. The obtained scheduling knowledge can assist the FMS operator in real-time to decide multiple decisions simultaneously, while maximally meeting multiple objective desired by the FMS operator. The acquired scheduling knowledge for an FMS scheduling problem is tested by comparing the desired and the simulated values of the multiple objectives. The result show that the knowledge acquisition and refinement method is effective for the multi-objective and multi-decision FMS scheduling problems.

• Proceedings of the Korea Society for Simulation Conference
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• 1997.04a
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• pp.93-99
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• 1997

Most of the past studies on FMS scheduling problems may be classified into two classes, namely off-line scheduling and on-line scheduling approach. The off-line scheduling methods are used mostly for FMS planning purposes and may not be useful real time control of FMSs, because it generates solutions only after a relatively long period of time. The on-line scheduling methods are used extensively for dynamic real-time control of FMSs although the performance of on-line scheduling algorithms tends vary dramatically depending on various configurations of FMS. Current study is about finding a better on-line scheduling rules for FMS operations. In this study, we propose a method to create priority functions that can be used in setting relative priorities among jobs or machines in on-line scheduling. The priority functions reflect the configuration of FMS and the user-defined objective functions. The priority functions are generated from diverse dispatching rules which may be considered a special priority functions by themselves, and used to determine the order of processing and transporting parts. Overall system of our work consists of two modules, the Priority Function Evolution Module (PFEM) and the FMS Simulation Module (FMSSM). The PFEM generates new priority functions using input variables from a terminal set and primitive functions from a function set by genetic programming. And the FMSSM evaluates each priority function by a simulation methodology. Based on these evaluated values, the PFEM creates new priority functions by using crossover, mutation operation and probabilistic selection. These processes are iteratively applied until the termination criteria are satisfied. We considered various configurations and objective functions of FMSs in our study, and we seek a workable solution rather than an optimum or near optimum solution in scheduling FMS operations in real time. To verify the viability of our approach, experimental results of our model on real FMS are included.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.24 no.64
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• pp.63-76
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• 2001

This paper presents a job-shop type flexible manufacturing system(FMS) scheduling problem and examines the effects of scheduling rules on the performance of FMS. Several machine and AGV scheduling rules are tested against the mean flow-time criterion. In this paper, I compare the rules under various experimental conditions by using an FMS simulation model. One of the objectives of this study is to discuss how the simulation-based scheduling problem can be operated. The other is to measure sensitivity of the rules to changes at inter arrival time, queue capacity, breakdown rates for machines and AGV, and AGV speed. Therefore, the results of simulation experiments were considered on FMS design and operating stages. A comprehensive bibliograph? is also presented in the paper.

• 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 Korean Institute of Industrial Engineers
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• v.30 no.2
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• pp.130-145
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• 2004

This paper addresses the integrated problem of process planning and scheduling in FMS (Flexible Manufacturing System). The integration of process planning and scheduling is important for an efficient utilization of manufacturing resources. In this paper, a new method using an artificial intelligent search technique, called asymmetric multileveled symbiotic evolutionary algorithm, is presented to handle the two functions at the same time. Efficient genetic representations and operator schemes are considered. While designing the schemes, we take into account the features specific to each of process planning and scheduling problems. The performance of the proposed algorithm is compared with those of a traditional hierarchical approach and existing evolutionary algorithms. The experimental results show that the proposed algorithm outperforms the compared algorithms.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.488-492
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• 1991

This paper deals with modeling and scheduling for flexible manufacturing systems(FMS). In modeling extended Petri nets are used to describe various and complex properties. To resolve multiple conflict without predefined properties, such as part selection, machine selection, rule-based scheduling method is introduced. This structure have a capability of on-line scheduling with systematic modeling description.

• 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.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.4
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• pp.344-350
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• 2001

In this paper, we are focused on the analysis of acyclic schedule for the determination of the opti-mal cycle time and minimization of work in process. Especially, this paper deals with the product ratio-driven cyclic scheduling problem in FMS with different products and ratio using the TPN(Time Petri Nets)un-folding.

• Journal of the Korea Society for Simulation
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• v.11 no.4
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• pp.57-68
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• 2002

The analysis of the cyclic scheduling problem in FMS using the transitive matrix has been proposed. Since the transitive matrix may explain all the relations between the places and transitions, we propose an algorithm to get good solution after slicing off some subnets from the original net based on machines operations. For analyzing the schedule problem, we considered two time functions such as produce time and waiting time using the P-invariant. In addition, we are shown the effectiveness of proposed algorithm after comparing with unfolding algorithms.