• The Transactions of the Korean Institute of Electrical Engineers P
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• v.59 no.3
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• pp.245-252
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• 2010

This paper proposes a constrained multi-area dispatch scheduling algorithm applicable to interconnected power system operations. The dispatch scheduling formulated as an MIP problem can be efficiently computed by GBD algorithm. GBD guarantees adequate computation speed and solution convergence by reducing the dimension of the dispatch scheduling problem. In addition, the regional decomposition technique based on ADM is introduced to obtain efficient inter-temporal OPF solution. It can find the most economic dispatch schedule incorporating power transactions without each regional utility's private information open.

• The Transactions of the Korea Information Processing Society
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• v.3 no.6
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• pp.1568-1579
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• 1996

Most of the real-time scheduling algorithms assume that all tasks are either preemptive or nonpreemptive. In this paper, we present a real-time scheduling algorithm for the more generalized task model in which each task contains both preemptive and nonpreemptive subtasks in a single processor environment. If the task set is found to be scheduling by the method of Harbour et al, it is also found to be scheduling by the proposed method. A simulation is used ti compare two methods and the result shows the maximum of 45% difference between them in their effectiveness.

• ETRI Journal
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• v.30 no.1
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• pp.129-140
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• 2008

In this paper, we propose a novel ant colony optimization (ACO)-based test scheduling method for testing network-on-chip (NoC)-based systems-on-chip (SoCs), on the assumption that the test platform, including specific methods and configurations such as test packet routing, generation, and absorption, is installed. The ACO metaheuristic model, inspired by the ant's foraging behavior, can autonomously find better results by exploring more solution space. The proposed method efficiently combines the rectangle packing method with ACO and improves the scheduling results by dynamically choosing the test-access-mechanism widths for cores and changing the testing orders. The power dissipation and variable test clock mode are also considered. Experimental results using ITC'02 benchmark circuits show that the proposed algorithm can efficiently reduce overall test time. Moreover, the computation time of the algorithm is less than a few seconds in most cases.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.131-134
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• 1996

Application of machine learning to scheduling problems has focused on improving system performance based on opportunistic selection among multitudes of simple rules. This study proposes a new method of learning scheduling rules, which first establishes qualitatively meaningful criteria and quantitatively optimizes the use of them, a similar way as human scheduler accumulate their expertise. The weighting of these criteria is trained in response to the system states through simulation. To mimic human quantitative feelings, distributed fuzzy sets are used for assessing the system state. The proposed method was applied to job dispatching in a simulated FMS environment. The job-dispatching criteria used were the length of the processing time of a job and the situation of the next workstation. The results show that the proposed method can develop efficient and robust scheduling strategies, which can also provide understandable and usable know-hows to the human scheduler.

• Korean Journal of Construction Engineering and Management
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• v.6 no.1 s.23
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• pp.73-79
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• 2005

This paper, introduces a Stochastic Project Scheduling Simulation system (SPSS III) developed by the author to predict a project completion probability in a certain time. The system integrates deterministic CPM, probabilistic PERT, and stochastic Discrete Event Simulation (DES) scheduling methods into one system. It implements automated statistical analysis methods for computing the minimum number of simulation runs, the significance of the difference between independent simulations, and the confidence interval for the mean project duration as well as sensitivity analysis method in What-if analyzer component. The SPSS 111 gives the several benefits to researchers in that it (1) complements PERT and Monte Carlo simulation by using stochastic activity durations via a web based JAVA simulation over the Internet, (2) provides a way to model a project network having different probability distribution functions, (3) implements statistical analyses method which enable to produce a reliable prediction of the probability of completing a project in a specified time, and (4) allows researchers to compare the outcome of CPM, PERT and DES under different variability or skewness in the activity duration data.

• Proceedings of the KIEE Conference
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• 2003.11b
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• pp.311-314
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• 2003

In recent years, distributed control systems(DCS) using fieldbus such as CAN have been applied to process systems but it is very difficult to design the DCS while guaranteeing the given end-to-end constraints such as precedence constraints, time constraints, and periods and priorities of tasks and messages. This paper presents a scheduling method to guarantee the given end-to-end constraints considering aperiodic, periodic and non-real-time message and task simultaneously. The presented scheduling method is the integrated one considering both tasks executed in each node and messages transmitted via the network and is designed to be applied to a general DCS that has multiple loops with several types of constraints, where each loop consists of sensor nodes with multiple sensors, actuator nodes with multiple actuators and controller nodes with multiple tasks.

• IE interfaces
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• v.22 no.4
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• pp.302-311
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• 2009

It's very important to make an effective and optimized production schedule for the small-to-medium-sized factory which have high-variety low-volume manufacturing properties. And now people say that MES is very useful to make scheduling more effectively. But for small-to-medium-sized factory, it is very difficult to build MES system because of fewer infrastructures in the factory, and more to keep it's continuous maintenance and improvement. Therefore it is more important to systematize the production scheduling generation using simpler and easier tools like EXCEL sheet. And it will be needed a new method to make simple MES construction for more efficient production scheduling. This paper proposes the method which can build simple MES easily using a tool of EXCEL VBA for a small-to-medium-sized factory, and introduces an applied case by the proposed method and EXCEL VBA.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2015.05a
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• pp.132-133
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• 2015

Efficient scheduling and resource management are the key factor to reduce construction project budget (e.g., labor cost, equipment cost, material cost, etc.). Resource-based line of balance (LOB) technique has been used to complement the limitations of time-driven scheduling techniques (e.g., critical-path method). Optimizing construction alternatives contributes cost savings while honoring the project deadline. However, existing LOB scheduling is lack of identifying optimal resource combination. This study presents a method which identifies the optimal construction alternatives, hence achieving resource minimization in a repetitive construction by using genetic algorithm (GA). The method provides efficient planning tool that enhances the usability of the system.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.7
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• pp.1314-1323
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• 2011

The maintenance of generating units is implicitly related with power system reliability and has a tremendous bearing on the operation of the power system. A technique using a fuzzy search method which is based on fuzzy multi-criteria function has been proposed for GMS (generator maintenance scheduling) in order to consider multi-objective function. In this study, a new technique using combined fuzzy set theory and genetic algorithm(GA) is proposed for generator maintenance scheduling. The genetic algorithm(GA) is expected to make up for that fuzzy search method might search the local solution. The effectiveness of the proposed approach is demonstrated by the simulation results on a practical size test systems.

• Journal of Electrical Engineering and Technology
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• v.5 no.1
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• pp.8-15
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• 2010

A new technique using a search method which is based on fuzzy multi-criteria function is proposed for GMS(generator maintenance scheduling) in order to consider multi-objective function. Not only minimization of probabilistic production cost but also maximization of system reliability level are considered for fuzzy multi-criteria function. To obtain an optimal solution for generator maintenance scheduling under fuzzy environment, fuzzy multi-criteria relaxation method(fuzzy search method) is used. The practicality and effectiveness of the proposed approach are demonstrated by simulation studies for a real size power system model in Korea in 2010.