• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.41 no.9
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• pp.681-688
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• 2013

Several problems caused by inevitable increment of airplane have been issued. The most effective solution to solve the issues is considered as establishing appropriate Air Traffic Management (ATM) that reduces aircraft's delay at an airport and intensify the airport's capacity. The purpose of this paper is to produce the optimum aircraft schedules that maximize the aircraft throughput by smooth air traffic flow near terminal area of an airport In this paper, mathematical formulations of the scheduling problem are firstly specified. Based on the mathematical modelling, an Optimization-Based Flight Scheduler that provides the optimum flight schedules for arriving aircraft is developed by introducing the Mixed Integer Linear Programming(MILP) and the Genetic Algorithms(GA). With this scheduler, we calculated the optimum schedules to compare to real schedule data from an Incheon Airport. As a result, it is validated that aircraft throughput produced by the optimum schedule is much better than that of the schedule from the Incheon airport. The optimization-based flight scheduler is expected to deal with problems due to the aircraft saturation in near future.

• 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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.5
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• pp.1007-1017
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• 1997

The existing survivability measure is defined as the only ratio of survival traffic volume on the given traffic demand. In this paper we suggest a new network survivability evaluation model. Sinceit depends on the importance of traffic, we can evaluatethe affect of telecommunication disaster. With the suggested evaluation model we formulate optimization models for restoration paths and traffic assinment on them. The optimization models are represented as mixed integer programming problems, which are difficult to find exact solutions. We develop heuristic algorithms according to the optimization models and apply them to an example network with 10 nodes and 17 links.

• Information Systems Review
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• v.5 no.2
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• pp.203-217
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• 2003

Constraint Programming and Optimization have developed in different fields to solve common problems in real world. In particular, constraint propagation and linear Programming are their own fundamental and complementary techniques with the potential for integration to benefit each other. This intersection has evoked the efforts to combine both for a solution method to combinatorial optimization problems. Attempts to combine them have mainly focused on incorporating either technique into the framework of the other with traditional models left intact. This paper argues that integrating both techniques into an old modeling fame loses advantages from another and the integration should be molded in a new framework to be able to exploit advantages from both. The paper propose a declarative modeling framework in which the structure of the constraints indicates how constraint programming and optimization solvers can interact to solve problems.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.4
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• pp.85-92
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• 2018

Reductions of the electricity charge are achieved by demand management of the load. The demand management method of the load using ESS involves peak shifting, which shifts from a high demand time to low demand time. By shifting the load, the peak load can be lowered and the energy charge can be saved. Electricity charges consist of the energy charge and the basic charge per contracted capacity. The energy charge and peak load are minimized by Linear Programming (LP) and Quadratic Programming (QP), respectively. On the other hand, each optimization method has its advantages and disadvantages. First, the LP cannot separate the efficiency of the ESS. To solve these problems, the charge and discharge efficiency of the ESS was separated by Mixed Integer Linear Programming (MILP). Nevertheless, both methods have the disadvantages that they must assume the reduction ratio of peak load. Therefore, QP was used to solve this problem. The next step was to optimize the formula combination of QP and LP to minimize the electricity charge. On the other hand, these two methods have disadvantages in that the charge and discharge efficiency of the ESS cannot be separated. This paper proposes an optimization method according to the situation by analyzing quantitatively the advantages and disadvantages of each optimization method.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.89-93
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• 2009

홍수기에 집중되는 하천유출량을 갈수기에 적절히 활용하기 위한 대표적인 시설이 댐이다. 제한된 용수공급량을 적절히 분배해 용수수요량을 만족시키면서 미래 갈수기시 용수공급을 위한 댐 저류량을 조절하는 것이 댐 운영의 중요한 목적 중 하나이다. 본 연구에서는 댐 저류량에 따라 댐 계획방류량을 일정비율 줄여주는 Hedging Rule을 5단계로 적용하여 댐의 상시만수위 저류량에 대한 실제 저류량의 편차 절대치 합, 수요에 대한 용수공급 부족량의 합, 그리고 하천유지유량에 대한 하천유량 부족량의 합을 목적함수로 하여 혼합정수 선형계획법(MILP, Mixed Integer Linear Programming)으로 식을 구성하였다. 한강수계의 다목적댐인 충주, 횡성, 소양강 댐과 용수전용댐인 광동 댐, 그리고 발전용 댐이지만 비교적 큰 저류용량을 가진 화천 댐을 댐 연계 운영 대상으로 하여 수자원장기종합계획의 2003년 유출량 및 수요량 자료와 댐운영실무편람의 댐 계획방류량 자료를 10일 단위로 입력하여 GAMS/CPLEX를 이용해 최적화하였다. 그 결과 생공용수 수요량 99.99%, 농업용수 수요량 99.91%, 그리고 하천유지용수 수요량 99.24%를 충족시키면서, 댐 저류율이 66.54%에서 86.39%로 증가하였다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.5C
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• pp.422-434
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• 2002

We propose 3-layered hierarchical fiber-optic backbone transmission network composed of B-DCS, Backbone ring, Edge ring for efficient transmission of high capacity traffic and consider design method to ensure network survivability of each layer at affordable cost. Mathematical ring-construction cost minimization using MIP(Mixed Integer Programming) models results in NP-complete problem. So, it is hard to solve it within reasonable computing time. on a large-scale network. Therefore we develop heuristic algorithms solving WSCAP(Working and Spared Channel Assignment Problem) for B-DCS, MRLB(Multi-Ring Load Balancing) problem for Backbone ring, and ORLB(Overlayed Ring Load Balancing) problem for Edge ring and show their usefulness through case study.

• Journal of the Korea Society of Computer and Information
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• v.11 no.1 s.39
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• pp.11-18
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• 2006

The logical analysis of data(LAD) is a Boolean-logic based data mining tool. A critical step in analyzing data by LAD is the pattern generation stage where useful knowledge and hidden structural information in data is discovered in the form of patterns. A conventional method for pattern generation in LAD is based on term enumeration that renders the generation of higher degree patterns practically impossible. In this paper, we present a novel optimization-based pattern generation methodology and propose two mathematical programming models, a mixed 0-1 integer and linear programming (MILP) formulation and a well-studied set covering problem (SCP) formulation for the generation of optimal and heuristic patterns, respectively. With benchmark datasets, we demonstrate the effectiveness of our models by automatically generating with ease patterns of high complexity that cannot be generated with the conventional approach.

• Korean Chemical Engineering Research
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• v.50 no.3
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• pp.479-491
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• 2012

In this paper we performed evaluation of the economics of a district heating system (DHS) consisting of energy suppliers and consumers, heat generation and storage facilities and power transmission lines in the capital region, as well as identification of optimal operating conditions. The optimization problem is formulated as a mixed integer linear programming (MILP) problem where the objective is to minimize the overall operating cost of DHS while satisfying heat demand during 1 week and operating limits on DHS facilities. This paper also propose a new forecasting model of the system marginal price (SMP) using past data on power supply and demand as well as past cost data. In the optimization, both the forecasted SMP and actual SMP are used and the results are analyzed. The salient feature of the proposed approach is that it exhibits excellent predicting performance to give improved energy efficiency in the integrated DHS.

• Journal of the Society of Naval Architects of Korea
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• v.31 no.4
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• pp.147-156
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• 1994

Though optimization method had been used for long time for the optimal design of ship structure, design variables in the most cases were assumed to be continuous real values or it was not easy to solve the mixed integer optimum design problems using the conventional optimization methods. Thus, it was often tried to use various initial starting points to locate the best optimum paint and to use special method such as branch and bound method to handle the discrete design variables in the optimization problems. Sometimes it had succeed, but the essential problems for dealing with the local optimum and discrete design variables was left unsolved. Hence, in this paper, Genetic Algorithms adopting the biological evolution process is applied to the ship structural design problem where the integer values for the number of stiffen design variables or the discrete values for the plate thickness variables would be more preferable in order to find out their effects on the final optimum design. Through the numerical result comparisons, it was found that Genetic Algorithm could always yield the global optimum for the discrete and mixed integer structural optimization problem cases even though it takes more time than other methods.