• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2006.06b
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• pp.345-348
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• 2006

LMTT (linear motor-based transfer technology) is horizontal transfer system in the maritime container terminal for the port automation. For LMTT system, shuttle cars are used instead of other types of cars. They are running on the routes which are stable on the terminal ground made of steel. The terminal scheduling complexity increases with the need of improving automation. It is necessary to make a good designed performance for the terminal system. This work presents a dispatching role using fuzzy logic for the shuttle cars. It considers the actual status of terminals and takes decisions on real time. A simulation is done to validate the role and two other dispatching rules to be compared.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1995.04a
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• pp.510-510
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• 1995

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1998.10a
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• pp.216-219
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• 1998

This study proposes JPT(Job-Pair Tardiness) that choose operation to be expected to generate better schedule consequence in comparing schedulable operation sets in pair to minimize total tardiness evaluation function in performing scheduling. In result of comparison with existing assignment rules. JPT generates better solution than most other rules in all kinds of problems. So it is anticipated that this is used for initial solution of heuristic and is used for finding more improved solution.

• Management Science and Financial Engineering
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• v.17 no.1
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• pp.79-94
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• 2011

Team orienteering, an extension of single-competitor orienteering, is the problem of determining multiple paths from a starting node to a finishing node for a given allowed time or distance limit fixed for each of the paths with the objective of maximizing the total collected score. Each path is through a subset of nodes, each of which has an associated score. The team orienteering problem has many applications such as home fuel delivery, college football players recruiting, service technicians scheduling, military operations, etc. Unlike existing optimal and heuristic algorithms often leading to heavy computation, this paper suggests two types of priority rule based heuristics-serial and parallel ones-that are especially suitable for practically large-sized problems. In the proposed heuristics, all nodes are listed in an order using a priority rule and then the paths are constructed according to this order. To show the performances of the heuristics, computational experiments were done on the small-to-medium sized benchmark instances and randomly generated large sized test instances, and the results show that some of the heuristics give reasonable quality solutions within very short computation time.

• The Transactions of the Korea Information Processing Society
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• v.7 no.10
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• pp.3113-3118
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• 2000

A framework proposed in this paper includes representations of multi-objectives rule-basd constraint satisfaction problem(RCSP) and especially, flexible structure of RCSP which provides adequate solution sithin an expectation time and adaptively considers some change of constratraints on the RCSP. In this study, the power system implemented by above framework is entirely programmed by using a modeling system for the quantitative model and a rule-based constraint programming tool for the qualitative model. The results of an exemplary cse show how the structure that involves the problem representation gives the scheduler an effective decision and what are the advantages of the easy and diverse representation for considering the techmical characteristics of the units on the RCSP over the traditional problem.

• Journal of Korea Society of Industrial Information Systems
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• v.16 no.2
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• pp.73-83
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• 2011

In the manufacturing system, production-planning is very important in effective management for expensive production facilities and machineries. To enhance efficiency of Manufacturing Execution System(MES), a manufacturing system that reduces the difference between planning and execution, certain production-planning needs a dispatching rule that is properly designed for characteristic of work information and there should be a appropriate selection for the rule as well. Therefore, in this paper dispatching rule will be selected by several simulations based on characteristics of work information derived from process planning data. By constructing information that are from simulation into ontology, one of the knowledge-based-reasoning, production planning platform based on the selection of dispatching rule will be demonstrated. The platform has strength in its wider usage that is not limited to where it is applied. To demonstrate the platform, RacerPro and Prot$\acute{e}$g$\acute{e}$ are used in parts of ontology reasoning, and JAVA and FlexChart were applied for production-planning simulation.

• The Journal of the Korea Contents Association
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• v.4 no.2
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• pp.50-60
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• 2004

Recently, most of the embedded system is required not only many functions but also real-time characteristics in purpose. In the hard real-time system, especially, strict deadline of periodic task can affect the performance of the system. In this paper, we design and implement the scheduler based on RM(Rate-Monotonic) rule. This scheduler makes feasible patterns based on EDF(Earliest deadline first) rule with extended schedulability inspection before execution, for periodic task-set that has high CPU utilization and then, execute periodic task-set depended on feasible patterns. The feasible pattern formed into EDF rule is capable of the efficiency of CPU up to 100 percentage and by the referenced execution of the feasible pattern is possible of removing the red-time scheduling overhead that is the defect of the order of dynamic assignment rule.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.12A
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• pp.1291-1297
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• 2004

In this paper, the new scheduling algorithm that supports the maximization of system throughput and the proportional fairness among non-real time traffic users is proposed in OFDMA wireless mobile communication systems. The concept of the proposed algorithm is based on the proportional fairness algorithm, which is deployed in 3GPP2, and sorting method. The proportional fairness algorithm is adapted to allocate the number of subcarrier per user. A sorting method is contributed to the maximization of system throughput in the practical allocation of subcarrier per user. Simulation results show that new algorithm had better performance than the max rate rule in case of fairness, higher throughput than the scheduling algorithm without sorting method. Even though the system throughput of the proposed algorithm is almost same with the iteration scheme using subcarrier swapping method between users, the computational time of the former is reduced up to 3 times than the latter.

• Journal of the Korea Society for Simulation
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• v.19 no.4
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• pp.99-109
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• 2010

Existing research about automated wafer transport management strategy for semiconductor manufacturing equipment was mainly focused on dispatching rules which is optimized to specific system layout, process environment or transfer patterns. But these methods can cause problem as like requiring additional rules or changing whole transport management strategy when applied to new type of process or system. In addition, a lack of consideration for interconnectedness of the added rules can cause unexpected deadlock. In this study, in order to improve these problems, propose dynamic priority based transfer job decision making algorithm which is applicable with regardless of system lay out and transfer patterns. Also, extra rule handling part proposed to support special transfer requirement which is available without damage to generality for maintaining a consistent scheduling policies and minimize loss of stability due to expansion and lead to improve productivity at the same time. Simulation environment of Twin-slot type semiconductor equipment was built In order to measure performance and examine validity about proposed wafer scheduling algorithm.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.176-184
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• 2023

Points of interest (POIs) are widely used in tourism recommendations and to provide information about areas of interest. Currently, situation judgement using POI and GPS data is mainly rule-based. However, this approach has the limitation that inferences can only be made using predefined POI information. In this study, we propose an algorithm that uses POI data, GPS data, and schedule information to calculate the current speed, location, schedule matching, movement trajectory, and POI coverage, and uses machine learning to determine whether to stay or go. Based on the input data, the clustered information is labelled by k-means algorithm as unsupervised learning. This result is trained as the input vector of the SVM model to calculate the probability of moving and staying. Therefore, in this study, we implemented an algorithm that can adjust the schedule using the travel schedule, POI data, and GPS information. The results show that the algorithm does not rely on predefined information, but can make judgements using GPS data and POI data in real time, which is more flexible and reliable than traditional rule-based approaches. Therefore, this study can optimize tourism scheduling. Therefore, the stay detection algorithm using GPS movement trajectories and POIs developed in this study provides important information for tourism schedule planning and is expected to provide much value for tourism services.