• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.249-251
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• 2007

The proposed LDS(Link-status Dependent Scheduling) algorithm in HR-WPAN up to now aims at doing only throughput elevation of the whole network, when the crucial DEV(Device) is connected with worst-link relatively, throughput of this DEV becomes aggravation, The proposed the WGS(Worst-case Guaranteed Scheduling) _algorithm in this paper guarantees throughput of the DEV which is connected with worst-link in a certain degree as maintaining throughput of all DEVs identically even if a link-status changes, decreases delay of the whole network more than current LDS algorithm Therefore proposed WGS algorithm in this paper will be useful in case of guaranteeing throughput of a DEV which is connected worst-link in a certain degree in a design of HR-WPAN hereafter.

• Industrial Engineering and Management Systems
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• v.10 no.3
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• pp.203-208
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• 2011

Job shop scheduling is well-known as one of the hardest combinatorial optimization problems and has been demonstrated to be NP-hard problem. In the past decades, several researchers have devoted their effort to develop evolutionary algorithms such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) for job shop scheduling problem. Differential Evolution (DE) algorithm is a more recent evolutionary algorithm which has been widely applied and shown its strength in many application areas. However, the applications of DE on scheduling problems are still limited. This paper proposes a one-stage differential evolution algorithm (1ST-DE) for job shop scheduling problem. The proposed algorithm employs random key representation and permutation of m-job repetition to generate active schedules. The performance of proposed method is evaluated on a set of benchmark problems and compared with results from an existing PSO algorithm. The numerical results demonstrated that the proposed algorithm is able to provide good solutions especially for the large size problems with relatively fast computing time.

• 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.

• Journal of Computing Science and Engineering
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• v.7 no.1
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• pp.44-52
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• 2013

This paper addresses the problem of resource scheduling in a grid computing environment. One of the main goals of grid computing is to share system resources among geographically dispersed users, and schedule resource requests in an efficient manner. Grid computing resources are distributed, heterogeneous, dynamic, and autonomous, which makes resource scheduling a complex problem. This paper proposes a new approach to resource scheduling in grid computing environments, the hierarchical stochastic Petri net (HSPN). The HSPN optimizes grid resource sharing, by categorizing resource requests in three layers, where each layer has special functions for receiving subtasks from, and delivering data to, the layer above or below. We compare the HSPN performance with the Min-min and Max-min resource scheduling algorithms. Our results show that the HSPN performs better than Max-min, but slightly underperforms Min-min.

• Journal of Computing Science and Engineering
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• v.7 no.1
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• pp.30-43
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• 2013

Multicore and multiprocessor systems with dynamic voltage scaling architectures are being used as one of the solutions to satisfy the growing needs of high performance applications with low power constraints. An important aspect that has propelled this solution is effective task/application scheduling and mapping algorithms for multiprocessor systems. This work proposes an energy aware, offline, probability-based unified scheduling and mapping algorithm for multiprocessor systems, to minimize the number of processors used, maximize the utilization of the processors, and optimize the energy consumption of the multiprocessor system. The proposed algorithm is implemented, simulated and evaluated with synthetic task graphs, and compared with classical scheduling algorithms for the number of processors required, utilization of processors, and energy consumed by the processors for execution of the application task graphs.

• Journal of the military operations research society of Korea
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• v.24 no.2
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• pp.162-169
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• 1998

This study presents an single machine scheduling algorithm minimize lateness of product by controlling machining speed. Generally, production scheduling uses the information of process planning. But the production scheduling algorithm has not considered the control of machining speed in its procedures. Therefore, the purpose of this study is to consider the machining speed in production scheduling algorithm for efficient production scheduling. Machining time and machining cost required to manufacture a piece of a product are expressed as a unimodal convex function with respect to machining speed, so it has minimal point at minimum time speed or the minimum cost speed. Therefore, because of considering the machining cost, the control of machining speed for the algorithm is executed between minimum speed and maximum speed. An example is demonstrated to explain the algorithm.

• Journal of KIISE:Computer Systems and Theory
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• v.32 no.11_12
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• pp.639-645
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• 2005

GRID environments have been developed in distributed heterogeneous computing infrastructure for advanced science and engineering Therefore efficient scheduling algorithms for allocating user job to resources in the GRID environment are required. Many scheduling algorithms have been proposed, but these algorithms are not suitable for the GRID environment. That is the previous scheduling algorithm does not consider network bandwidth between multiple resources. In this paper, we propose a new scheduling algorithm for Global GRID environment and show that our algorithm has better performance than other scheduling algorithms through extensive simulation.

• The KIPS Transactions:PartA
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• v.13A no.5 s.102
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• pp.381-386
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• 2006

In this paper, we designed and implemented a web-based grid scheduling platform(WGridSP), which can model a system and simulate scheduling scheme in grid computing. WGridSP used GridSim, a grid scheduling toolkit in java-environment, as a tool for simulation and is able to Perform resource modeling, task modeling, algorithm compiling, simulation, and Performance evaluation rapidly in web environment. WGridSP can be applied as a foundation for grid research and can be used to analyze the efficiency of scheduling algorithm.

• Journal of the Korean Operations Research and Management Science Society
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• v.27 no.4
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• pp.67-86
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• 2002

This paper considers subway crew scheduling problem. Crew scheduling is concerned with finding a minimum number of assignments of crews to a given timetable satisfying various restrictions. Traditionally, crew scheduling problem has been formulated as a set covering or set partitioning problem possessing exponentially many variables, but even the LP relaxation of the problem is hard to solve due to the exponential number of variables. In this paper. we propose two basic techniques that solve the subway crew scheduling problem in a reasonable time, though the optimality of the solution is not guaranteed. We develop an algorithm that solves the column-generation problem in polynomial time. In addition, the integrality of the solution is accomplished by variable-fixing technique. Computational result for a real instance is reported.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.12
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• pp.3096-3117
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• 2013

To execute the performance driven Grid applications, an effective and scalable workflow scheduling is seen as an essential. To optimize cost & makespan, in this paper, we propose a Scalable Cost-Time Trade-off (SCTT) model for scheduling workflow tasks. We have developed a heuristic algorithm known as Scalable Cost-Time Trade-off Scheduling (SCTTS) with a lower runtime complexity based on the proposed SCTT model. We have compared the performance of our proposed approach with other heuristic and meta-heuristic based scheduling strategies using simulations. The results show that the proposed approach improves performance and scalability with different workflow sizes, task parallelism and heterogeneous resources. This method, therefore, outperforms other methods.