• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.816-817
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• 2007

As UNFCC(United Nations Framework Convention on Climate Change) is enhanced, Korea will perform a CO2 reduction duty. The CO2 reduction duty will effect Korea power system because coal and oil thermal generations emit large CO2 form about 46% of total CO2 emission. Moreover various alternatives should be designed to comply with CO2 reduction duty. In this paper, we analysis resource planning considering CO2 emission constraints and emission trading. And we analysis resource planning under using LP(Linear Programing) and MIP(Mixed Integer Programing).

• Journal of Korea Multimedia Society
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• v.18 no.12
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• pp.1468-1474
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• 2015

Efficient spectrum sharing is an important issue in Device-to-Device (D2D) communications underlaying cellular networks as it can mitigate the interference to cellular users and improve the performance of the systems. In this paper, we formulate the radio resource allocation in D2D communications as a mixed nonlinear integer programing. We show the formulated problem is NP-hard and thus a polynomial time algorithm to solve is not possible. Since such a problem is very hard to obtain the optimal solution within a short running time, we instead propose a fast heuristic suboptimal algorithm to mitigate the interference caused to cellular users and improve the performance of the systems. Simulation results are provided to evaluate the performance of the proposed algorithm.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2014.10a
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• pp.53-55
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• 2014

Offshore 에서의 oil & gas 생산은 해상이라는 환경으로 인한 고유의 특성 때문에 항상 다수의 변수들에 영향을 받으며, 막대한 비용이 소요되기 때문에 비용을 최소화하며, 비용 대비 수익을 최대화시키기 위한 optimal design이 필수이다. 본 논문은 가상의 offshore plant와 이에서 생산된 oil의 수요지들을 설정하여 시장수요에 따른 offshore 생산의 최적화 문제를 연구대상으로 하며, 다수의 offshore oil fields를 보유한 major oil company가 당면할 수 있는 offshore production에 관한 문제를 일반화하여 정의하고, 이윤을 극대화시킬 수 있는 최적화 모형을 혼합정수계획모형(mixed integer programming)으로 정식화 하였다. 최적화 모형의 해는 Microsoft office excel solver를 통해 구하였으며 그 계산실험의 결과를 요약하여 보고한다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.3 no.1
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• pp.10-19
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• 2002

The purpose of this paper is to describe the design of a general multipurpose batch process or plant in terms of a series of mathematical programing models, and to develop approach solution methodologies. The proposed model for a single period is based on the formulation (MINLP; Mixed Integer Nonlinear Programming) of Papageorgaki and Reklaitis [1], but was linearized (MILP; Mixed Integer Linear Programming) so as to obtain an exact and practical solution, and to allow treatment of uncertainties to be considered in expanding the plant. As a solution strategy a modified Benders' Decomposition was introduced and was tested on three example problems. The optimizing solver, OSL code provided by the IBM Corporation, was used for solving the problems. The solution method was successful in that it showed remarkable reduction in the computing times as compared with the direct solution method.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.11a
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• pp.350-353
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• 2003

Navy surface vessels require pier services such as emergency repair, oil supply, fm loading/unloading, crane, standby readiness, normal repair, gun arrangement, ammunition loading, and food loading during the period in port. The purpose of this study is to establish efficient berth allocation plan for navy surface vessels in home port under the limited resources of piers and equipments. The study suggests Mixed Integer Programing (MIP) model for bath allocation problem, considering precedence relationships among services. For a effective analysis, the model is implemented by ILOG OPL(Optimization Programming Language) Studio 3.1 and ILOG Cplex 7.0. The results of the model show reduction of berth shifts and increasement of service benefits. And thus, it would be a possibility of contribution in the improvement of fleet readiness.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.4
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• pp.692-699
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• 2008

Semiconductor research and development(R&D) fabs are very different than production fabs in many ways such as the scales of production, job priority, production methods, and performance measures. Efficient operations of R&D fabs are very important to the development of new product, process stability, high yield, and ultimately company competitiveness. This paper proposes the fab-wide scheduling method for operational optimization of the R&D fabs. Most scheduling systems of semiconductor fabs have only focused on maximizing throughput of each separated areas without considering WIP(works in process) flows of entire fab. In this paper, we proposes the a fab-wide scheduling system which schedules all lots to entire fab equipment at once. We develop the MIP(mixed integer programing) model which allocates the lots to production equipment considering many constraints of all processes and the CP(constraint programming) model which determines the sequences of the lots in the production equipment. The proposed FAB-wide scheduling model is applied to the newly constructed R&D fab. As a result, we have accomplished the system based automated job reservation, decrease of the hot lot delay, increase of the queue time satisfaction, the high throughput by maximizing the batch sizes, decrease of the WIP TAT(Turn Around Time).

• Journal of Korea Water Resources Association
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• v.47 no.10
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• pp.891-906
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• 2014

This study suggests the hedging rule of MIP (Mixed Integer Programing) in counting the risk evaluation criteria of the objective function and constraints in order to provide the optimum operating rule in reservoir system as constraining water shortage as much as possible which may happen in the downstream control point of water supply in the aspect of water system management. The proposed model is applied to the Han-river reservoir system for two testing periods (Case I: Jan. 1993~Dec. 1997, Case II: Jan. 1999~Dec. 2003). The model based on the hedging rule with trigger volume, estimated in this study shows that in Case I, the monthly minimum discharge was $310.6{\times}10^6m^3$ in the single operation, $56.3{\times}10^6m^3$ in the joint operation, and $317.5{\times}10^6m^3$ in the hedging rule and also, in Case II, the monthly minimum discharge was found to be $204.2{\times}10^6m^3$ in the single operation, $111.2{\times}10^6m^3$ in the joint operation, and $243.7{\times}10^6m^3$ in the hedging rule. In conclusion, the hedging rule, proposed in this study can decrease vulnerability while guarantees reliability and resiliency.

• Journal of Navigation and Port Research
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• v.39 no.4
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• pp.353-360
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• 2015

The offshore oil production requires a huge amount of cost and time accompanied by multiple variables due to the peculiar nature of 'offshore'. And every process concerned is controlled by elaborate series of plans for reducing loss of lives, environment and property. This paper treats an optimization problem for offshore oil production and transportation. We present an offshore production and transportation network to define scope of the problem and construct a mixed integer linear programming model to tackle it. To demonstrate the validity of the optimization model presented, some computational experiments based on hypothetical offshore oil fields and demand markets are carried out by using MS Office Excel solver. The downstream of the offshore production and transportation network ends up with the maritime transportation problem distributing the crude oil produced from offshore fields to demand markets. We used MoDiSS(Model-based DSS in Ship Scheduling) which was built to resolve this maritime transportation problem. The paper concludes with the remark that the results of the study might be meaningfully applicable to the real world problems of offshore oil production and transportation.

• Korean Chemical Engineering Research
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• v.58 no.3
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• pp.346-355
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• 2020

This study proposed a new optimization-based decision model for an enterprise resource planning and production scheduling of a pharmaceutical intermediates manufacturing plant. To do this work, we first define the inflow and outflow information as well as the model structure, and develop an optimization model to minimize the production time (i.e., makespan) using a mixed integer linear programing (MILP). The unique feature of the proposed model is that the optimal process scheduling is established based on real-time resource logistics information using a radio frequency identification (RFID) technology, thereby theoretically requiring no material inventories. essential information for process operation, such as the required amount of raw materials and estimated arrival timing to manufacturing plant, is used as logistics constraints in the optimization model to yield the optimal manufacturing scheduling to satisfy final production demands. We illustrated the capability of the proposed decision model by applying the optimization model to two scheduling problems in a real pharmaceutical intermediates manufacturing process. As a result, the optimal production schedule and raw materials order timing were identified to minimize the makespan while satisfying all the product demands.

• Journal of Korean Society of Transportation
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• v.22 no.7 s.78
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• pp.161-167
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• 2004

While most or fixed-time control systems such as UTCS produce the signal timing plans that either maximizing bandwidth or minimizing a disutility index of delay and stops, cannot consider the fluctuation of traffic flow. One category of the traffic-response control systems, which make small changes on a predefined signal plan such as SCOOT, cannot be easily modified for feedback real-time control schemes based on observation of variables other than traffic flow. The other category, which decide to whether switch the traffic lights or not at each step of time as in PRODYN, does not adequately consider the relations between traffic flows and traffic lights at each step of time. In this paper we present a complete formulation that adequately consider the relations between traffic flows and traffic lights at each step of time. The formulation is a binary mixed integer linear programing (BMILP) that obtain traffic lights at each step for minimizing delay. Since numarical examples for application of the proposed model illustrated that the model adequately produced dynamic traffic signal plans minimizing delay at each step, the model may be expected to contribute to advanced transportation management systems (ATMS) for dynamic traffic signal control.