• 대한전기학회논문지
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• 제35권12호
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• pp.594-602
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• 1986

This paper proposes an effective algorithm for short-term generation scheduling for the purpose of economic and secure operation of thermal power systems. Especially, in the procedure of solution by Dynamic Programming, Linear Programming is introduced to promote the possibility of optimal solution and the security of power systems, and evaluation of security function is improved by the application of seven step approximation of normal distribution. Several necessary considerations, that is, time dependent start-up and constant down cost of generating units, demand and spinning reserve constraints, minimum up and sown time constraints, the number of possible start-up of a generating unit in a d and the number of generating units which can be started up at the same time at the same bus, are also incoporated to elevate the usability and flexibility of the algorithm. Finally, the effectiveness of the proposed algorithm has been demonstrated by applying to the 6-gen. 21-bus model power system.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 A
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• pp.331-333
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• 2000

This paper propose the method combined Priority and Tabu search (TS) for short term hydro-thermal scheduling. We satisfy various conditions using TS, Restarting method is used as diversification strategy of TS to prevent a local convergence. Also, we use Lagrangian method to solve economic dispatch problems.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권8호
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• pp.2993-3010
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• 2021

The job shop scheduling problem (JSSP) plays a critical role in smart manufacturing, an effective JSSP scheduler could save time cost and increase productivity. Conventional methods are very time-consumption and cannot deal with complicated JSSP instances as it uses one optimal algorithm to solve JSSP. This paper proposes an effective scheduler based on deep learning technology named self-supervised long-short term memory (SS-LSTM) to handle complex JSSP accurately. First, using the optimal method to generate sufficient training samples in small-scale JSSP. SS-LSTM is then applied to extract rich feature representations from generated training samples and decide the next action. In the proposed SS-LSTM, two channels are employed to reflect the full production statues. Specifically, the detailed-level channel records 18 detailed product information while the system-level channel reflects the type of whole system states identified by the k-means algorithm. Moreover, adopting a self-supervised mechanism with LSTM autoencoder to keep high feature extraction capacity simultaneously ensuring the reliable feature representative ability. The authors implemented, trained, and compared the proposed method with the other leading learning-based methods on some complicated JSSP instances. The experimental results have confirmed the effectiveness and priority of the proposed method for solving complex JSSP instances in terms of make-span.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1995년도 하계학술대회 논문집 B
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• pp.553-555
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• 1995

This paper presents the optimal short-term operation scheduling by using on cogeneration systems connected with auxiliary equipments. Simulation is performed in case of the bottomming cycle which generates the demand heat preferentially. Heat storage tank, electricity charger, auxiliary boiler and independent generator are considered as auxiliary equipments connected to cogeneration systems. The results of simulation show the auxiliary equipments can be effeciently operated in case of the bottomming cycle by modeling proposed in this paper. The effectiveness of operation scheduling gained by application of fuzzy theory is evaluated by detailed comparison and investigation of the simulation results.

• 전자공학회논문지B
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• 제30B권3호
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• pp.31-40
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• 1993

This paper deals with the modeling and scheduling for FMC(Flexible Manufacturing Cells). The FMC system composed of unit or multi cells is capable of improving productivity with flexibility for machine. However, the properties of multiple jobs and various alternatives results in tne dynamic states which make system management very complex. The extended Peti nets are used to represent for complex properties of FMC which performs short-term scheduling and dynamic operational scheduling. The hierarchical control structure and integlligent scheduling through expert module are adopted for efficiency of FMC operations. The computer simulation reveals that intelligent scheduling method is better than heuristics in various performance indices.

• 한국컴퓨터정보학회논문지
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• 제20권9호
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• pp.61-66
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• 2015

We investigate rate scheduling and power allocation problem for a delay constrained CDMA systems. Specifically, we determine an energy efficient scheduling policy, while each user maintains the short term (n time slots) average throughput. More importantly, it is shown that the optimal transmission strategy for the uplink is same as that of the downlink, called uplink and downlink duality. We then examine the performance of the optimum transmission strategy for the uplink and the downlink for various system environments.

• 대한산업공학회지
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• 제33권3호
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• pp.290-302
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• 2007

This paper introduces several decision-making problems that need to be solved in order to facilitate the efficient operation of container terminals. These decision-making problems include the berth planning problem, the quay crane scheduling problem, the unload/load sequencing problem, the yard allocation problem, and the short-term scheduling of transporters and yard cranes. These problems can be classified into strategic decision problems, tactical decision problems, and real time operational decision problems. This paper proposes definitions of the problems that can be used to develop mathematical models for the problems.

• Journal of Electrical Engineering and Technology
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• 제12권1호
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• pp.64-71
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• 2017

Considering the volatility, intermittent and random of photovoltaic (PV) generation systems, accurate forecasting of PV power output is important for the grid scheduling and energy management. In order to improve the accuracy of short-term power forecasting of PV systems, this paper proposes a prediction model based on environmental factors and support vector machine optimized by genetic algorithm (GA-SVM). In order to improve the prediction accuracy of this model, weather conditions are divided into three types, and the gray correlation coefficient algorithm is used to find out a similar day of the predicted day. To avoid parameters optimization into local optima, this paper uses genetic algorithm to optimize SVM parameters. Example verification shows that the prediction accuracy in three types of weather will remain at between 10% -15% and the short-term PV power forecasting model proposed is effective and promising.

• 한국CDE학회논문집
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• 제14권6호
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• pp.424-433
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• 2009

In order to improve productivity and efficiency of ship production process, production technology converged with Information Technology can be considered. Mid-term scheduling based on long-term schedule of ship building and execution planning based on short-term production schedule have an important role in ship production processes and techniques. However, data used in the scheduling are from the experiences of the past, cognitive, and often inaccurate, moreover the updates of the data by formatted documents are not being performed efficiently. This paper designs the tracking and monitoring system for the curved plates forming process with shop level. At first step to it, we redefine and analyze the curved plates forming process by using SysML. From the definition and analysis of the curved plates forming process, we design the system with respect to operational view considering operational environment and interactions between systems included and scenario about operation, and with respect to system view considering functionalities and interfaces of the system. In order to study the feasibility of the system designed, a prototype of the system has been implemented with 13.56 MHz RHD hardware and application software.

• 대한산업공학회지
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• 제2권1호
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• pp.93-100
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• 1976

Given a fixed production process and facility capacity, the ability to respond to market fluctuations in terms of changes in production, work force, and inventory is the major task of production management. The costs involved are primarily payroll (regular and overtime), inventory carrying, and hiring and firing. The magnitude of these costs is usually a significant portion of the operating costs of the firm and consequently a small percentage saving due to astute aggregate scheduling can mean substantial absolute saving. At least three demonstrably optimal techniques have been developed for solving this aggregate scheduling problem. These three optimal are apparently LDR, PPP, and SDR. By combining these three different approaches, another optimal solution was obtained by me. I call this CDR (Combined Decision Rule). This approach appears to be useful. This approach may be generalizable to aggregate scheduling involving a short term resources.