• IE interfaces
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• v.11 no.1
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• pp.75-84
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• 1998

The important issue for intra-city vehicle scheduling is to measure and store actual vehicle travel speeds between customer locations. Travel speeds(and times) in nearly all metropolitan areas change drastically during the day because of congestion in certain parts of the city road network. We propose three models for estimating departure time-dependent travel speeds between locations that relieve much burden for the data collection and computer storage requirements. Two of the three models use a least squares method and the rest one employs a neural network trained with the back-propagation rule. On a real-world study using the travel speed data collected in Seoul, we found out that the neural network model is more accurate than the other two models.

• IE interfaces
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• v.14 no.4
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• pp.385-393
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• 2001

In this paper, a scheme of scheduling a bottleneck operation is presented for production planning of make-to-order. We focus on the problem of capacity-dependent processing time in which processing time of the bottleneck operation is not fixed, but varies with job sequence or equipment capacity. For this, a genetic algorithm is applied for job sequencing with an objective function of mean square of weighted deviation. An experimental study is implemented in power transformer plant and results are compared with those of the EDD rule. It shows that the genetic algorithm is relatively good for most cases.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.51
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• pp.231-240
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• 1999

A major concern in Concurrent Engineering is the control and management of workload in a period of process. As a general rule, leveling the peak of workload in certain period is difficult because concurrent processing is comprised of various processes, including overlapping, paralleling looping and so on. Therefore, the workload management with resource constraints is so beneficial that effective methods to analyze design process are momentous. This study presents the Timed Petri Nets approach of precedence logic networks, and provides an alternative for users to analyze constraint processes to resolve conflicts of resources. Another approach to Continuous Time Markov Chain using Stochastic Petri Nets is also proposed. These approaches are expected to facilitate resolving resource constrained scheduling problems more systematically in Concurrent Engineering environment.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.47
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• pp.125-138
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• 1998

In this paper, we investigate the effect of re-entrance to the same work station in a job shop with multiple identical machines. System A is defined as the system in which re-entrance is not permitted, and system B is defined as the system in which re-entrance is permitted. By the analytical result of the queueing network, we find that the two systems have the same queue length distributions and utilizations under FIFO dispatching rule when all parameters are same. Simulation models are developed for various comparisons between the two systems, and simulation experiments are conducted for the combinations of five dispatching rules, two average workloads and two due date allowances. Five performance measures are selected for the comparison. The simulation results show that permitting re-entrance affects for some combinations of system environments.

• Proceedings of the Safety Management and Science Conference
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• 2004.05a
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• pp.291-294
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• 2004

Last 2003, the CRM mayor was not lively glaringly. At beginning of the year, it may be said that gained result fewer than half of that is forecasted. Enterprises are seen that there are a lot of occasions that did not carry CRM project that planned very first time in practice or put off investment program until 2004 altogether. This can see that it is thing which CRM's accuracy of data analysis process drops up to now and investment of enterprises is unprepared. In this paper, It consolidates the necessity on a LTV (Life Time Value) and analyzes data which is concerned of Customer Value. Under the these environments, defines the LTV rule that can improve the customer value. And then, Scheduling plays an important role in shop floor planning. Therefore, this study tries to proposed that Scheduling by customer needs group for minimizing the problem.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.24 no.62
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• pp.97-109
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• 2001

This research is concerned with jobshop scheduling problem for an advanced manufacturing system like flexible manufacturing which consists of two machine centers and a single automated guided vehicle(AGV). The objective is to develop and evaluate heuristic scheduling procedures that minimize makespan to be included travel time of AGV. A new heuristic algorithm is proposed and illustrates the proposed algorithm. The heuristic algorithm is implemented for various cases by SLAM II. The results show that the proposed algorithm provides better solutions in reduction ratio and frequency than the previous algorithm.

• Journal of Korean Institute of Industrial Engineers
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• v.27 no.2
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• pp.158-168
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• 2001

We present a tabu search (TS) algorithm to minimize maximum lateness on a single machine in the presence of sequence dependent setup times and dynamic job arrivals. The TS algorithm starts with a feasible schedule generated by a modified ATCS (Apparent Tardiness Cost with Setups) rule, then through a series of search steps it improves the initial schedule. Results of extensive computational experiments show that the TS algorithm significantly outperforms a well-known RHP heuristic by Ovacik and Uzsoy, both on the solutions quality and the computation time. The performance advantage is particularly pronounced when there is high competition among jobs for machine capacity.

• Proceedings of the Korean Nuclear Society Conference
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• 1996.11a
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• pp.73-78
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• 1996

In this study, we proposed a fuzzy gain scheduler with intelligent learning algorithm for a reactor control. In the proposed algorithm, we used the gradient descent method to learn the rule bases of a fuzzy algorithm. These rule bases are learned toward minimizing an objective function, which is called a performance cost function. The objective of fuzzy gain scheduler with intelligent learning algorithm is the generation of adequate gains, which minimize the error of system. The condition of every plant is generally changed as time gose. That is, the initial gains obtained through the analysis of system are no longer suitable for the changed plant. And we need to set new gains, which minimize the error stemmed from changing the condition of a plant. In this paper, we applied this strategy for reactor control of nuclear power plant (NPP), and the results were compared with those of a simple PI controller, which has fixed gains. As a result, it was shown that the proposed algorithm was superior to the simple PI controller.

• Industrial Engineering and Management Systems
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• v.14 no.4
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• pp.401-412
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• 2015

In this paper, we present a modeling approach to production planning for an actual production line and a heuristic method. We also illustrate the successful implementation of the proposed method on the production line. A heuristic algorithm called the push-back algorithm was designed for a single machine earliness/tardiness production planning with distinct due date. It was developed by combining a minimum slack time rule and shortest processing time rule with a push-back procedure. The results of a numerical experiment on the heuristic's performance are presented in comparison with the results of IBM ILOG CPLEX. The proposed algorithm was applied to an actual case of production planning at Woongjin Chemical, a leading manufacturer of filter products in South Korea. The seven-month execution of our algorithm led to a 24.5% decrease in the company's inventory level, thus demonstrating its practicality and effectiveness.

• International Journal of Control, Automation, and Systems
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• v.5 no.3
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• pp.324-328
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• 2007

An analytical framework for fuzzy modeling and control of nonlinear systems using a set of linear models is presented. Fuzzy clustering is applied on the aerodynamic coefficients of a missile to obtain an optimal number of rules in a Tagaki-Sugeno fuzzy rule-set. Next, the obtained membership functions and rule-sets are applied to a set of linear optimal controllers towards extraction of a global controller. Reported simulations demonstrate the performance, stability, and robustness of the controller.