• The Journal of Society for e-Business Studies
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• v.24 no.3
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• pp.19-33
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• 2019

Recently, manufacturers have been struggling to efficiently use production equipment as their production methods become more sophisticated and complex. Typical factors hindering the efficiency of the manufacturing process include setup cost due to job change. Especially, in the process of using expensive production equipment such as semiconductor / LCD process, efficient use of equipment is very important. Balancing the tradeoff between meeting the deadline and minimizing setup cost incurred by changes of work type is crucial planning task. In this study, we developed a scheduling model to achieve the goal of minimizing the duedate and setup costs by using reinforcement learning in parallel machines with duedate and work preparation costs. The proposed model is a Deep Q-Network (DQN) scheduling model and is a reinforcement learning-based model. To validate the effectiveness of our proposed model, we compared it against the heuristic model and DNN(deep neural network) based model. It was confirmed that our proposed DQN method causes less due date violation and setup costs than the benchmark methods.

• Journal of the Korea Society for Simulation
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• v.28 no.4
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• pp.45-56
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• 2019

Literatures have considered mathematical model that change the job order of shipper for improving the operation time of yard crane. However, on the real site, it is impossible to change the job order decided according to the shipper's arrival order. Therefore, operation managers have been utilized the relatively simple strategy that job control is better but the process time of yard crane is longer due to the growth of yard crane's interference time and empty drive time. This study proposed a new yard-crane scheduling approach that decided the job order before the shipper's truck arrived the yard terminal. We utilize the Container Pre-Information Notice estimating the arrival time of truck. We developed the container terminal simulation model for validation of the effect of proposed scheduling approach. The results show that the proposed scheduling reduced the interference delay time and empty moving time of yard crane and shipper's truck delay time.

• Spatial Information Research
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• v.9 no.1
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• pp.15-30
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• 2001

Solid waste collection service is viewed as one of the most important public services in urban area. The purpose of this study is to apply the GIS based regional partitioning and arc routing methods for solid waste collection districting and vehicle routing-scheduling in order to provide waste collection service more efficiently. In this study, solid waste deposit sites are derived from the centroid of each building and the amount of solid waste is deduced based on the number of households and establishments. The regional partitioning procedure is performed based on waste collection zones which are constructed from waste deposit sites. The result of this study shows that solid waste collection districts which are delineated by regional partitioning method are able to increase efficiencies and cut costs in performing solid waste collection services. Also the output of vehicle-scheduling from the analysis of arc routing may provide more efficiently and quickly manage the scheduling of the residential solid waste collection routes, reducing costs with minimal deadheading costs. Therefore, the application of GIS based on regional partitioning and arc routing methods would be very useful to construct a solid waste management system by supplying the important and flexible informations for solid waste collection districts and vehicle routing-scheduling for waste collection.

• The Journal of Korean Association of Computer Education
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• v.11 no.5
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• pp.67-76
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• 2008

Grid computing has a large scale virtual computing environment that enables a collaborative processing through sharing resources of geographically distributed organizations. In recent year, the development of wireless networks and mobile devices enables mobile devices to consider as a resource of the grids. However, there are some problems such as low performance of processors, small capacity of storages, limited capacity of battery, and low bandwidth. In this paper, to overcome these limitations occurred in mobile grid environments, we proposed a proxy-based mobile grid system. Our proposed system enables mobile devices to play roles as a resource consumer and a resource provider and to collaborate with wired grids through a mobile router. Also, we propose an adaptive job scheduling scheme to cope with context changes of mobile devices and compare our scheduling scheme with other scheduling schemes using a simulation tool, SimGrid, to verify the validity of our job scheduling scheme.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.9
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• pp.4103-4121
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• 2018

Quality of Service (QoS) awareness is recognized as a key point for the success of Internet of Things (IOT).Realizing the full potential of the Internet of Things requires, a real-time task scheduling algorithm must be designed to meet the QoS need. In order to schedule tasks with diverse QoS requirements in cloud environment efficiently, we propose a task scheduling strategy based on dynamic priority and load balancing (DPLB) in this paper. The dynamic priority consisted of task value density and the urgency of the task execution, the priority is increased over time to insure that each task can be implemented in time. The scheduling decision variable is composed of time attractiveness considered earliest completion time (ECT) and load brightness considered load status information which by obtain from each virtual machine by topic-based publish/subscribe mechanism. Then sorting tasks by priority and first schedule the task with highest priority to the virtual machine in feasible VMs group which satisfy the QoS requirements of task with maximal. Finally, after this patch tasks are scheduled over, the task migration manager will start work to reduce the load balancing degree.The experimental results show that, compared with the Min-Min, Max-Min, WRR, GAs, and HBB-LB algorithm, the DPLB is more effective, it reduces the Makespan, balances the load of VMs, augments the success completed ratio of tasks before deadline and raises the profit of cloud service per second.

• Journal of the Korea Society for Simulation
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• v.20 no.1
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• pp.87-96
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• 2011

DEVS(Discrete Event Systems Specification) is a set theoretic formalism developed for specifying discrete event system. For execution of DEVS, we need an execution environment, which consists of simulation engine and models interpreted by the simulation engine. Common existing environments use hierarchical scheduling algorithm for DEVS execution. This hierarchical scheduling is a proper algorithm for DEVS execution because of hierarchical and modular characteristics. But this algorithm has overheads owing to message passing and time management. To overcome these overheads, we apply event-oriented simulation to DEVS execution and we remove hierarchical overheads. In eventoriented simulation, the scheduling of model execution is performed by events and event list. We propose three event-oriented execution environments for DEVS and experiment about the performance of our proposed environments in comparison with the existing execution environment using the hierarchical scheduling. The experimental results show our environments works better than existing environment using the hierarchical scheduling.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.1
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• pp.3-8
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• 2016

Wireless networks have evolved to the appearance of heterogeneous wireless networks(HetNet), where various networks provide data services with various data rates and coverage. One of technical issues for HetNet is efficient utilization of radio resources for system performance enhancement. For the next generation wireless networks, energy saving has become one of key performance indices, so energy-efficient resource management schemes for HetNet need to be developed. This paper addresses an energy-efficient scheduling for HetNet in order to improve the energy efficiency while maintaining similar system throughput as existing scheme, for which an energy-efficient scheduling that energy efficiency factor is included. Simulation results show that the proposed scheme achieves the reduction of energy consumption while admitting limited ragne of throughput degradation in comparison with the conventional proportional fair scheduling.

• Journal of Korea Society of Industrial Information Systems
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• v.26 no.5
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• pp.11-19
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• 2021

In this paper, we proposed an asymmetric multi-core processor scheduling scheme which is based on the mileage of each core. We considered a big-LITTLE multi-core processor structure, which consists of low power consuming LITTLE cores with general performance and high power consuming big cores with high performance. If a task needs to be processed, the processor decides a core type (big or LITTLE) to handle the task, and then investigate the core with the shortest mileage among unoccupied cores. Then assigns the task to the core. We developed a mileage-based balancing algorithm for asymmetric multi-core assignment and showed that the proposed scheduling scheme is more cost-effective compared to the traditional scheme from a management perspective. Simulation is also conducted for the purpose of performance evaluation of our proposed algorithm.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.1
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• pp.143-150
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• 2019

We focus on the weapon target assignment and fire scheduling problem (WTAFSP) with the objective of minimizing the makespan, i.e., the latest completion time of a given set of firing operations. In this study, we assume that there are m available weapons to fire at n targets (> m). The artillery attack operation consists of two steps of sequential procedure : assignment of weapons to the targets; and scheduling firing operations against the targets that are assigned to each weapon. This problem is a combination of weapon target assignment problem (WTAP) and fire scheduling problem (FSP). To solve this problem, we define the problem with a mixed integer programming model. Then, we develop exact algorithms based on a dynamic programming technique. Also, we suggest how to find lower bounds and upper bounds to a given problem. To evaluate the performance of developed exact algorithms, computational experiments are performed on randomly generated problems. From the results, we can see suggested exact algorithm solves problems of a medium size within a reasonable amount of computation time. Also, the results show that the computation time required for suggested exact algorithm can be seen to increase rapidly as the problem size grows. We report the result with analysis and give directions for future research for this study. This study is meaningful in that it suggests an exact algorithm for a more realistic problem than existing researches. Also, this study can provide a basis for developing algorithms that can solve larger size problems.

• The KIPS Transactions:PartC
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• v.10C no.5
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• pp.595-602
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• 2003

In this paper, we proposed new buffer management and cell scheduling scheme of GFR service for improving fairness of TCP/IP traffic in ATM networks. The proposed algorithm used untagged cell, which came to ATM switch, to decide the policy for discard of frame and what kind of VC cell it would serve. Performance analysis through the simulation present that proposed scheme can meet fairness 2 (MCR Plus equal share), which are not met by conventional scheduling mechanism such as WRR. Also, proposed scheme is superior to WRR about 30% in throughput and more efficiency in fairness criteria.