• Journal of Korean Society of Transportation
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• v.22 no.7 s.78
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• pp.131-137
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• 2004

Conventional traffic signal optimization models assume that green intervals for pedestrian crossings are given as exogenous inputs such as minimum green intervals for straight-ahead movements. As the result, in reality, the green intervals of traffic movements may not distribute adequately by the volume/saturation-flow of them. In this paper, we proposed signal optimization models formulated in BMILP to integrate pedestrian crossings into traffic movements under under-saturated traffic flow. The model simultaneously optimizes traffic and pedestrian movements to minimize weighted queues of primary queues during red interval and secondary queues during queue clearance time. A set of linear objective function and constraints set up to ensure the conditions with respect to pedestrian and traffic maneuvers. Numerical examples are given by pedestrian green intervals and the number of pedestrian crossings located at an arm. Optimization results illustrated that pedestrian green intervals using proposed models are greater than those using TRANSYT-7F, but opposite in the ratios of pedestrian green intervals to the cycle lengths. The simulation results show that proposed models are superior to TRANSYT-7F in reducing delay, where the longer the pedestrian green interval the greater the effect.

• Water for future
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• v.29 no.4
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• pp.109-118
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• 1996

The neural network is a mathematical model of theorized brain activity which attempts to exploit the parallel local processing and distributed storage properties. The neural metwork is a good model to be applied for the classification problem, large combinatorial optimization and nonlinear mapping. A multi-layer neural network is constructed to predict rainfall. The network learns continuourvalued input and output data. Application of neural network to 1-hour real data in Seoul metropolitan area and the Soyang River basin shows slightly good predictions. Therefore, when good data is available, the neural network is expected to predict the complicated rainfall successfully.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.6
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• pp.853-858
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• 2019

One of the methods which can enhance the efficiency of railroad network is construction of interconnection branch line for several route to share one railway. In Korea, this method already has been implemented or excuted as project level. This study suggests a network design model and a solution algorithm to choice most proper site to construction it and determine the priority of branch lines which can be considered in planning level, not project level. The model is a non-linear optimization program which minimize total cost-construction cost, operating cost and passengers' travel cost. The decision variables are a binary variable to explain whether construction or not and its direction and a integer variable of the frequencies of travel routes. The solution algorithm-problem solution and route choice and also the result of implementation for example network are suggested. This result can be more advanced after application in real network and calibration of parameters.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.4 no.3
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• pp.27-42
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• 1984

The complexity and expensiveness of water resources projects have made optimum operation and design by computer-based techniques of increasing interest in recent years. Water resources problems in real world need many decisions under numerous constraints. In addition there are nonlinearities in the state and return function. This mathematical and technical troublesome must be overcome so that the optimum operation polices are determined. Then traditional dynamic optimization method encountered two major-cruxes: variable discretization and appearance of constraints. Even several recent methods which based on the Differential Dynamic Programming(DDP) have some difficulties in handling of constraints. This paper has presented New DDP which is applicable to multi-reservoir control. It is intended that the method suggested here is superior to abailable alternatives. This belief is supported by analysis and experiments(New DDT does not suffer course of dimensionality and requires no discretization and is able to handle easily all constraints nonlinearity).

• Journal of Korea Water Resources Association
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• v.32 no.3
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• pp.281-289
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• 1999

Small-scale hydropower projects at existing agricultural reservoirs can contribute to produce electric energy by maximizing the use of releases from the reservoirs. The irrigation water duration, the reservoir hydropower simulation, and the nonlinear programming model are employed to estimate potential hydroelectric energy at an existing reservoir. The nonlinear programming model consists of finding a maximum hydroelectric energy subject to irrigation water demand constraints. The sample reservoir given a set of inflow and irrigation water is considered. The optimal solutions by the optimization model yield the most hydroelectric energy for the analysis period in the three methods. Consequently, the nonlinear programming model uses the most water for hydropower generation with respect to the total inflow of the sample reservoir. It is also found that additional storage by increasing the normal water level of the sample reservoir does not significantly increase the annual hydroelectric energy for the given reservoir. It is expected that the optimization model and the proposed procedure for estimating potential hydroelectric energy can be applied to evaluate feasibility analysis for small scale hydropower additions at existing agricultural dams.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.14 no.1
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• pp.231-243
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• 1994

A stochastic programming model for river water quality management was developed. River water quality, river flow, quality and flowrate of the wastewater treatment plant inflow were treated as random variables in the model. Withdrawal for water supply and submerged weir reaeration were included in the model itself. A probabilistic model was formulated to compute the expectation and variance of water quality using Streeter-Phelps equation. Chance constraints of the optimization problem were converted to deterministic equivalents by chance constrained method. Objective function was total annual treatment cost of all wastewater treatment plants in the region. Construction cost function and O & M cost function were derived in the form of nonlinear equations that are functions of treatment efficiency and capacity of treatment plant. The optimization problem was solved by nonlinear programming. This model was applied to the lower Han River. The results show that the reliability to meet the DO standards of the year 1996 is about 50% when the treatment level of four wastewater treatment plants in Seoul is secondary treatment, and BOD load from the tributary inflows is the same as present time. And when BOD load from Tanchon, Jungrangchon, and Anyangchon is decreased to 50%, the reliability to meet the DO standards of the year 1996 is above 60%. This results indicated that for the sake of the water quality conservation of the lower Han River, water quality of the tributaries must be improved, and at least secondary level of treatment is required in the wastewater treatment plants.

• Journal of Korean Institute of Industrial Engineers
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• v.6 no.2
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• pp.21-29
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• 1980

This paper deals with the capital budgeting problem of a firm where investments are risky and interrelated. The established models might be classified into two categories; One is the chance-constrained programming model and the other is the expected utility maximization model. The former has a rather limited objective function and does not consider the risk in direct manner. The latter, on the other hand, might lead to a wrong decision because it uses an approximate value of expected utility. This paper attempts to extend the applicability of the chance-constrained programming model by modifying its objective function into a more general form. The capital budgeting problem is formulated as a nonlinear 0-1 integer programming problem first, and is formulated into a linear 0-1 integer programming problem for finding a lower-bound solution of the original problem. The optimal solution of the original problem is then obtained by branch & bound algorithm.

• Journal of the Korean earth science society
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• v.29 no.3
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• pp.263-279
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• 2008

This study is concerned with the optimization of models using MM5 and WRF mesoscale numerical models to simulate strong sea surface winds, such as that of typhoon Shanshan on 17 September 2006, and the Siberian high event on 16 December 2006, which were selected for displaying the two highest mean wind speeds. The model optimizations for the lowest level altitude, physical parameters and horizontal resolution were all examined. The sea surface wind values obtained using a logarithmic function which takes into account low-level stability and surface roughness were more accurate than those obtained by adjusting the lowest-level of the model to 10 m linearly. To find the optimal parameters for simulating strong sea surface winds various physical parameters were combined and applied to the model. Model grid resolutions of 3-km produced better results than those of 9-km in terms of displaying accurately regions of strong wind, low pressure intensities and low pressure mesoscale structures.

• Journal of Korean Society of Transportation
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• v.27 no.6
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• pp.147-156
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• 2009

We present a methodology for modeling and solving the transit frequency design problem with variable demand. The problem is described as a bi-level model based on a non-cooperative Stackelberg game. The upper-level operator problem is formulated as a non-linear optimization model to minimize net cost, which includes operating cost, travel cost and revenue, with fleet size and frequency constraints. The lower-level user problem is formulated as a capacity-constrained stochastic user equilibrium assignment model with variable demand, considering transfer delay between transit lines. An efficient algorithm is also presented for solving the proposed model. The upper-level model is solved by a gradient projection method, and the lower-level model is solved by an existing iterative balancing method. An application of the proposed model and algorithm is presented using a small test network. The results of this application show that the proposed algorithm converges well to an optimal point. The methodology of this study is expected to contribute to form a theoretical basis for diagnosing the problems of current transit systems and for improving its operational efficiency to increase the demand as well as the level of service.

• Journal of the Korean Society for Railway
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• v.7 no.1
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• pp.9-13
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• 2004

Railway passenger demand forecasts may be used directly, or as inputs to other optimization models use them to produce estimates of other activities. The optimization models require demand forecasts at the most detailed level. In this environment exponential smoothing forecasting methods such as Holt-Winters are appropriate because it is simple and inexpensive in terms of computation. There are several initialization methods for Holt-Winters Model. The purpose of this paper is to compare the initialization methods for Holt-Winters model.