• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.5
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• pp.929-935
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• 2011

Customers hardly change to electric prices in old days because electricity is essential commodity, while demand changes with price after deregulation. It's explained by price-based demand response with demand-elasticity matrix. Also all of the customers have had identical demand-price elasticity matrix till now. But in a practical power system, various customers are present with taking a variety of demand-price elasticity. Therefore this paper proposes demand-price sensitivity to represent different demand-price elasticity. Also as proposing demand-reliability sensitivity, it is modeling various customers' characteristics to reliability. And then this paper calculates total expected interruption cost of customer from the customer interruption cost and the demand-reliability sensitivity. A total expected interruption cost of system is shown as opportunity cost of a generation cost.

• KIEE International Transactions on Power Engineering
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• v.5A no.4
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• pp.331-338
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• 2005

In this paper, an improved maintenance scheduling approach suitable for the competitive environment is proposed by taking account of profits and costs of generation companies and the formulated combinatorial optimization problem is solved by using Reactive Tabu search (RTS). In competitive power markets, electricity prices are determined by the balance between demand and supply through electric power exchanges or by bilateral contracts. Therefore, in decision makings, it is essential for system operation planners and market participants to take the volatility of electricity price into consideration. In the proposed maintenance scheduling approach, firstly, electricity prices over the targeted period are forecasted based on Artificial Neural Network (ANN) and also a newly proposed aggregated bidding curve. Secondary, the maintenance scheduling is formulated as a combinatorial optimization problem with a novel objective function by which the most profitable maintenance schedule would be attained. As an objective function, Opportunity Loss by Maintenance (OLM) is adopted to maximize the profit of generation companies (GENCOS). Thirdly, the combinatorial optimization maintenance scheduling problem is solved by using Reactive Tabu Search in the light of the objective functions and forecasted electricity prices. Finally, the proposed maintenance scheduling is applied to a practical test power system to verify the advantages and practicability of the proposed method.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 1996.04a
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• pp.59-76
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• 1996

Vessels in the world merchant fleet generally operate in either liner or bulk trade. The supply and the demand trend of general cargo ship are both on the ebb however those trend of tankers and containers are ins light ascension. Oil tankers are so far the largest single vessel type in the world fleet and the tanker market is often cited as a texbook example of perfect competition. Some shipping statistics in recent years show that there has been a radical fluctuation in spot charter rate under easy charter's market. This implies that the proper scheduling of tankers under spot market fluctuation has the great potential of improving the owner's profit and economic performance of shipping. This paper aims at developing the TS-DSS(Decision Support System for Tanker Scheduling) in the context of the importance of scheduling decisions. TS-DSS is defined as a DSS based on the optimization models for tanker scheduling. The system has been developed through the life cycle of systems analysis design and implementation to be user-friendly system. The performance of the system has been tested and examined by using the data edited under several tanker scheduling has been tested and examined by using the data edited under several tanker scheduling scenarios and thereby the effectiveness of TS-DSS is validated satisfactorily. The authors conclude the paper with the comments of the need of appropriate support environment such as data-based DSS and network system for successful implementatio of the TS-DSS.

• Journal of the Korean Operations Research and Management Science Society
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• v.5 no.1
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• pp.53-59
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• 1980

An order level inventory model is developed for deteriorating items. The demand during prescribed scheduling period is constant and deterministic in which the demand follows power pattern. Deterioration is assumed to be a constant fraction of the on hand inventory. The expression for the optimal order level is developed and an example is given to illustrate the model.

• Industrial Engineering and Management Systems
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• v.10 no.1
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• pp.74-83
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• 2011

In this paper, we consider a new lot-sizing and scheduling problem (LSSP) that minimizes the sum of production cost, setup cost and inventory cost. Setup carry-over, setup overlapping, state dependent setup time as well as demand splitting are considered. For this LSSP, we develop a mixed integer programming (MIP) model, of which the size does not increase even if we divide a time period into a number of micro time periods. Also, we develop an efficient heuristic algorithm by combining a decomposition scheme with a local search procedure. Test results show that the developed heuristic algorithm finds a good quality (in practice, even better) feasible solution using far less computation time compared with the CPLEX, a competitive MIP solver.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.1074-1077
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• 2002

This paper proposes an adaptive pricing system with scheduling to balance the demand for contents and to realize an effective use of resources in contents delivery networks. In the proposed adaptive pricing system, the table of the service levels and prices (tariff) is shown to each user at the start of service and each user chooses one of the service classes. These prices are decided adaptively reflecting the congestion state of the networks. Then, by the proposed scheduling algorithm, these requests are scheduled so as to keep the service level agreements completely.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.23 no.59
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• pp.21-36
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• 2000

The drum-buffer-rope(DBR) system is a finite scheduling mechanism that balances the flow of the production system. DBR controls the flow of materials through the plant in order to produce products in accordance with market demand, with a minimum of manufacturing lead time, inventory, and operating expenses. This paper integrates the best of MRP push system and JIT pull system with DBR system, efficiently adapts these logics to capacity constraint resources, and contributes to the evolution of synchronous manufacturing. The purpose of this paper is, thus, threefold. The first objective is to identify the frame of theory of constraints(TOC) and the logic of DBR scheduling. The second objective is to formulate the DBR constraint scheduling problems(DBRCSP) in a job shop environments. Finally, the paper is to suggest the solution procedure of DBRCSP for embedding TOC into MRP/JIT along with an numerical expression. In addition, illustrative numerical example is given.

• Journal of the Korean Operations Research and Management Science Society
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• v.21 no.2
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• pp.171-186
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• 1996

This paper comes from an observation that overemphasis on capacity utilization meausre, which is usual under capacity shortage, can seriously hurt the firm's profit and potential process improvement. We suggest a model that can be used in designing a coordination scheme for decentralized marketing and manufacturing activities. Using a price and time-sensitive demand and capacitated lotsizing model, we derive an effective communication medium betwen marketing and manufacturing. This Balance Indicator of process capacity and flexibility also implies that the increase in capacity availability and setup time reduction should be balanced by its market requirements. This is particularly important when a firm tries to improve its process capability by kaizen. Further, the model can be used to show the comparative performances of scheduling policies under capacity imbalnce. We show the shortening the scheduling cycle can improve the firm profit without changing the simple scheduling rule.

• ETRI Journal
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• v.26 no.2
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• pp.185-188
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• 2004

In this paper, we design a two-step scheduling algorithm to support multiple bandwidth allocation policies for upstream channel access in an Ethernet passive optical network. The proposed scheduling algorithm allows us a simultaneous approach for multiple access control policies: static bandwidth allocation for guaranteed bandwidth service and dynamic bandwidth allocation for on-demand, dynamic traffic services. In order to reduce the scheduling complexity, we separate the process of the transmission start- time decision from the process of grant generation. This technique does not require the timing information of other bandwidth allocation modules, so respective modules are free from a heavy amount of timing information or complex processing.

• Journal of The Korean Association of Information Education
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• v.4 no.2
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• pp.140-146
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• 2001

Scheduling strategy in the Education-on-Demand system should be designed to service the isochronous requests from several learners with single disk retrieval to improve the performance of the system. In this paper, the scheduling strategy which reduces the disk I/O and buffer consumption by utilizing the resources of the learner's system has been proposed. All the requests from the learner are not serviced from the server but forwarded to the learner's system which preserves the requested information. Therefore, the server can increase the throughput and reduces the initial latency time of the user. The proposed strategy has been compared to the conventional method by simulations and proved to be more efficient.