• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.8
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• pp.3516-3541
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• 2018

Task scheduling is one of the most challenging aspects of cloud computing nowadays, and it plays an important role in improving overall performance in, and services from, the cloud, such as response time, cost, makespan, and throughput. A recent cloud task-scheduling algorithm based on the symbiotic organisms search (SOS) algorithm not only has fewer specific parameters, but also incurs time complexity. SOS is a newly developed metaheuristic optimization technique for solving numerical optimization problems. In this paper, the basic SOS algorithm is reduced, and chaotic local search (CLS) is integrated into the reduced SOS to improve the convergence rate. Simulated annealing (SA) is also added to help the SOS algorithm avoid being trapped in a local minimum. The performance of the proposed SA-CLS-SOS algorithm is evaluated by extensive simulation using the Matlab framework, and is compared with SOS, SA-SOS, and CLS-SOS algorithms. Simulation results show that the improved hybrid SOS performs better than SOS, SA-SOS, and CLS-SOS in terms of convergence speed and makespan.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.37 no.3
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• pp.43-50
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• 2014

In this paper, we deal with a single machine scheduling problems integrating with step deterioration effect and a rate-modifying activity (RMA). The scheduling problem assumes that the machine may have a single RMA and each job has the processing time of a job with deterioration is a step function of the gap between recent RMA and starting time of the job and a deteriorating date that is individual to all jobs. Based on the two scheduling phenomena, we simultaneously determine the schedule of step deteriorating jobs and the position of the RMA to minimize the makespan. To solve the problem, we propose a hybrid typed genetic algorithm compared with conventional GAs.

• Proceedings of the KSME Conference
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• 2000.04a
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• pp.797-802
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• 2000

Flow shop scheduling problem involves processing several jobs on common facilities where a setup time Is incurred whenever there is a switch of jobs. Practical aspect of scheduling focuses on finding a near-optimum solution within a feasible time rather than striving for a global optimum. In this paper, a hybrid meta-heuristic method called tabu-genetic algorithm(TGA) is suggested, which combines the genetic algorithm(GA) with tabu list. The experiment shows that the proposed TGA can reach the optimum solution with higher probability than GA or SA(Simulated Annealing) in less time than TS(Tabu Search). It also shows that consideration of setup time becomes more important as the ratio of setup time to processing time increases.

• Management Science and Financial Engineering
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• v.20 no.2
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• pp.33-37
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• 2014

A flow shop scheduling problem involves scheduling jobs on multiple machines in series in order to optimize a given criterion. The flow time of a job is the amount of time the job spent before its completion and the stretch of the job is the ratio of its flow time to its processing time. In this paper, a hybrid genetic algorithm (HGA) approach is proposed for minimizing the total stretch in flow shop scheduling. HGA adopts the idea of seed selection and development in order to reduce the chance of premature convergence that may cause the loss of search power. The performance of HGA is compared with that of genetic algorithms (GAs).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39B no.10
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• pp.629-644
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• 2014

The goal of this paper is to consider a co-design approach between time delay compensation and the message scheduling for CAN-Based Networked Control Systems (NCS). First we propose a hybrid priority scheme for the message scheduling in order to improve the Quality of Service (QoS). Second we present the way to calculate the closed-loop communication time delay and then compensate this time delay using the pole placement design method in order to improve the Quality of Control (QoC). The final objective is the implementation of a co-design which is the combination of the compensation for communication time delays and the message scheduling in order to have a more efficient NCS design.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.999-1003
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• 1992

In the paper, a hybrid control approach for the swing-up control of a rotary type inverted pendulum is treated using one-chip microcomputer. The control approach is composed by a scheduling logic control for swing up control and the linear state feedback control to achieve the disired inverted-state of the pendulum. The experimental cystem has been implemented by a 16-bit one-chip microcomputer with 3096 opu as the digital controller incorporating the above mentioned control approach.

• Journal of Electrical Engineering and Technology
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• v.12 no.5
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• pp.1709-1718
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• 2017

This paper presents a hybrid stochastic deterministic multi-timescale scheduling (SDMS) approach for generation scheduling of a power grid. SDMS considers flexible resource options including conventional generation flexibility in a chance-constrained day-ahead scheduling optimization (DASO). The prime objective of the DASO is the minimization of the daily production cost in power systems with high penetration scenarios of variable generation. Furthermore, energy storage is scheduled in an hourly-ahead deterministic real-time scheduling optimization (RTSO). DASO simulation results are used as the base starting-point values in the hour-ahead online rolling RTSO with a 15-minute time interval. RTSO considers energy storage as another source of grid flexibility, to balance out the deviation between predicted and actual net load demand values. Numerical simulations, on the IEEE RTS test system with high wind penetration levels, indicate the effectiveness of the proposed SDMS framework for managing the grid flexibility to meet the net load demand, in both day-ahead and real-time timescales. Results also highlight the adequacy of the framework to adjust the scheduling, in real-time, to cope with large prediction errors of wind forecasting.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.10
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• pp.75-84
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• 1997

This paper describes the development of an integrating method for process planning and scheduling activities for block assembly in shipbuilding. A block is composed of several steel plates and steel sections with the predetermined shapes according to the ship design. The parts which constitute the block are manufac- tured by cutting and/or bending operations, which are termed as machining operation in this paper. The machining operation is the first process for block assembly which influences the remaining block assembly processes. Thus process planning and scheduling for machining operation to manufacture parts for block are very important to meet the assembly schedule in the shipyard. An integrating method for process plan- ning and scheduling is developed by introducing the concept of distributed process planning and scheduling composed of initial planning, alternative planning and final planning stages. In initial planning stage, nesting parts information and machining emthods are generated for each steel plate. In alternative plan- ning stage, machine groups are selected and workcenter dispatching information is generated. In final planning stage, cutting sequences are determined. The integrated system is tested by case study. The result shows that the integrated system is more efficient than existing manual planning system.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.04a
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• pp.609-612
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• 2000

Job-shop scheduling problem(JSSP) is one of the best-known machine scheduling problems and essentially an ordering problem. A new encoding scheme which always give a feasible schedule is presented, by which a schedule directly corresponds to an assigned-operation ordering string. It is initialized with G&T algorithm and improved using the developed genetic operator; APMX or BPMX crossover operator and mutation operator. and the problem of infeasibility in genetic generation is naturally overcome. Within the framework of the newly designed genetic algorithm, the NP-hard classical job-shop scheduling problem can be efficiently solved with high quality. Moreover the optimal solutions of the famous benchmarks, the Fisher and Thompson's 10${\times}$10 and 20${\times}$5 problems, are found.

• Journal of Communications and Networks
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• v.8 no.4
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• pp.401-409
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• 2006

Orthogonal frequency division multiplexing (OFDM) and multiple input multiple output (MIMO) technologies provide additional dimensions of freedom with spectral and spatial resources for radio resource management. Multi-dimensional radio resource management has recently been identified to exploit the full dimensions of freedom for more flexible and efficient utilization of scarce radio spectrum while provide diverse quality of service (QoS) guarantees. In this work, a multi-dimensional radio resource scheduling scheme is proposed to achieve above goals in hybrid orthogonal frequency division multiple access (OFDMA) and space division multiple access (SDMA) systems. Cochannel interference (CCI) introduced by frequency reuse under SDMA is eliminated by frequency division and time division between highly interfered users. This scheme maximizes system throughput subjected to the minimum data rate guarantee. for heterogeneous users and transmit power constraint. By numerical examples, system throughput and fairness superiority of the our scheduling scheme are verified.