• Journal of the Korea Society of Computer and Information
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• v.19 no.6
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• pp.101-108
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• 2014

The parallel machine scheduling is to schedule each job to exactly one parallel machine so that the total completion time is minimized. It is used in various manufacturing system areas such as steel industries, semiconductor manufacturing and plastic industries. Each job has a setup phase and a processing phase. A removal phase is needed in some application areas. A processing phase is performed by a parallel machine alone while a setup phase and a removal phase are performed by both a server and a parallel machine simultaneously. Most of previous researches used a single server and considered only a setup phase and a processing phase. If a single server is used for scheduling, the bottleneck in the server increases the total completion time. Even though the number of parallel machines is increased, the total completion time is not reduced significantly. In this paper, we have proposed an efficient algorithm for the parallel machine scheduling using multiple servers and considering setup, processing and removal phases. We also have investigated experimentally how the number of servers and the number of parallel machines affect the total completion time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.7
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• pp.3057-3075
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• 2020

End-to-end network delay plays an vital role in distributed services. This delay is used to measure QoS (Quality-of-Service). It would be beneficial to know all node-pair delay information, but unfortunately it is not feasible in practice because the use of active probing will cause a quadratic growth in overhead. Alternatively, using the measured network delay to estimate the unknown network delay is an economical method. In this paper, we adopt the state-of-the-art matrix completion technology to better estimate the network delay from limited measurements. Although the number of measurements required for an exact matrix completion is theoretically bounded, it is practically less helpful. Therefore, we propose an online adaptive sampling algorithm to measure network delay in which statistical leverage scores are used to select potential matrix elements. The basic principle behind is to sample the elements with larger leverage scores to keep the traits of important rows or columns in the matrix. The amount of samples is adaptively decided by a proposed stopping condition. Simulation results based on real delay matrix show that compared with the traditional sampling algorithm, our proposed sampling algorithm can provide better performance (smaller estimation error and less convergence pressure) at a lower cost (fewer samples and shorter processing time).

• International conference on construction engineering and project management
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• 2015.10a
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• pp.114-116
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• 2015

This paper presents a Stochastic Time-Cost Tradeoff analysis system (STCT) that identifies optimal construction methods for activities, hence reducing the project completion time and cost simultaneously. It makes use of schedule information obtained from critical path method (CPM), applies alternative construction methods data obtained from estimators to respective activities, computes an optimal set of genetic algorithm (GA) parameters, executes simulation based GA experiments, and identifies near optimal solution(s). A test case verifies the usability of STCT.

• Journal of Korean Institute of Industrial Engineers
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• v.34 no.3
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• pp.318-327
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• 2008

This paper considers a single-machine scheduling problem with availability constraints. In many realistic situations, machines may not be always available due to various reasons such as maintenance, breakdown and repair. However, most literature on scheduling assume that the machines are available at all times. This paper deals with a single-machine scheduling problem with periodic maintenance. If the maintenance decision is made jointly with the job scheduling, the system will be more effective. The objective is to minimize the total completion time of jobs. This problem is proved to be NP-hard in the strong sense. The proposed breaking heuristic(BH) algorithm rule is established by some theorems and conditions. Our computational results show that the BH algorithm is much more efficient than existing heuristic.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.925-926
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• 2006

In the multi-agent system for a single task, the action selection can be made for the real-time environment by using the global coordination space, global coordination graph and MAX-PLUS algorithm. However, there are some difficulties in multi-agent system for multi-tasking. In this paper, a real-time decision making method is suggested by using coordination space, coordination graph and dynamic coordinated state of multi-agent system including many agents and multiple tasks. Specifically, we propose locally dynamic coordinated state to effectively use MAX-PLUS algorithm for multiple tasks completion. Our technique is shown to be valid in the box pushing simulation of a multi-agent system.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.43
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• pp.287-297
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• 1997

This research is concerned with operation control problem for an automated manufacturing system which consists of two machine centers and a single automatic guided vehicle. The objective is to develop and evaluate heuristic scheduling procedures that minimize maximum completion time to be included travel time of AGV. A new heuristic algorithm is proposed and a numerical example 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 than the previous algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.4
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• pp.1519-1534
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• 2016

In this paper, we study how to optimize the data shuffle phase by leveraging the flow relationship in datacenter networks (DCNs). In most of the clustering computer frameworks, the completion of a transfer (a group of flows that can enable a computation stage to start or complete) is determined by the flow completing last, so that limiting the rate of other flows (not the last one) appropriately can save bandwidth without impacting the performance of any transfer. Furthermore, for the flows enter network late, more bandwidth can be assigned to them to accelerate the completion of the entire transfer. Based on these characteristics, we propose the flow chasing algorithm (FCA) to optimize the completion of the entire transfer. We implement FCA on a real testbed. By evaluation, we find that FCA can not only reduce the completion time of data transfer by 6.24% on average, but also accelerate the completion of data shuffle phase and entire job.

• Journal of the Korean Operations Research and Management Science Society
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• v.19 no.2
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• pp.107-118
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• 1994

This research is concerned with production scheduling for a flexible manufacturing cell which consists of two machine centers with unlimited buffer space and a single automatic guided vehicle. The objective is to develop and evaluate heuristic scheduling procedures that minimize maximum completion time. A numerical example 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 than Johnson's. It also gets good solutions to minimize mean flowtime.

• Journal of applied mathematics & informatics
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• v.25 no.1_2
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• pp.183-199
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• 2007

In this paper we research the problem in which the objective is to minimize the sum of squared deviations of job expected completion times from the due date, and the job processing times are stochastic. In the problem the machine is subject to stochastic breakdowns and all jobs are preempt-repeat. In order to show that the replacing ESSD by SSDE is reasonable, we discuss difference between ESSD function and SSDE function. We first give an express of the expected completion times for both cases without resampling and with resampling. Then we show that the optimal sequence of the problem V-shaped with respect to expected occupying time. A dynamic programming algorithm based on the V-shape property of the optimal sequence is suggested. The time complexity of the algorithm is pseudopolynomial.

• ETRI Journal
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• v.34 no.3
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• pp.330-340
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• 2012

In many applications of wireless sensor actor networks (WSANs) that often run in harsh environments, the reduction of completion times of tasks is highly desired. We present a new time-aware, energy-aware, and starvation-free algorithm called Scate for assigning tasks to actors while satisfying the scalability and distribution requirements of WSANs with semi-automated architecture. The proposed algorithm allows concurrent executions of any mix of small and large tasks and yet prevents probable starvation of tasks. To achieve this, it estimates the completion times of tasks on each available actor and then takes the remaining energies and the current workloads of these actors into account during task assignment to actors. The results of our experiments with a prototyped implementation of Scate show longer network lifetime, shorter makespan of resulting schedules, and more balanced loads on actors compared to when one of the three well-known task-scheduling algorithms, namely, the max-min, min-min, and opportunistic load balancing algorithms, is used.