• Journal of Korean Institute of Industrial Engineers
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• v.34 no.2
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• pp.181-189
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• 2008

Survivability of a network is one of the most important issues in designing present-day communication networks. For the past few decades, a lot of researches have proposed the mathematical models to evaluate the survivability of networks. In this paper, we attempt to survey such researches and classify them based on how these researches measure the survivability of a network.

• Korea Real Estate Review
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• v.28 no.1
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• pp.23-37
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• 2018

The genetic algorithm (GA) and branch and bound (B&B) methods are the useful methods of searching the optimal project combination (combinatorial optimization) to maximize the project effect considering the budget constraint and the balance of regional development with regard to the Urban Regeneration New Deal policy, the core real estate policy of the Moon Jae-in government. The Ministry of Land, Infrastructure, and Transport (MOLIT) will choose 13 central-city-area-type projects, 2 economic-base-type projects, and 10 public-company-proposal-type projects among the numerous projects from 16 local governments while each government can apply only 4 projects, respectively, for the 2017 Urban Regeneration New Deal project. If MOLIT selects only those projects with a project effect maximization purpose, there will be unselected regions, which will harm the balance of regional development. For this reason, an optimization model is proposed herein, and a combinatorial optimization method using the GA and B&B methods should be sought to satisfy the various constraints with the object function. Going forward, it is expected that both these methods will present rational decision-making criteria if the central government allocates a special-purpose-limited budget to many local governments.

• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.8
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• pp.1854-1868
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• 1995

An effective nesting algorithm has been proposed to allocate the arbitrary shapes on one or several raw sheets by applying the well-known simulated annealing algorithm as the optimization technique. In this approach, both the shapes to be allocated and the raw sheets are represented as the grid-based models. This algorithm can accommodate every possible situations encountered in cutting apparel parts from the raw leather sheets. In other words, the usage of the internal hole of a shape for other small shapes, handling of the irregular boundaries and the interior defects of the raw sheets, and the simultaneous allocation on more than one raw sheets have been tackled on successfully in this study. Several computational experiments are presented to verify the robustness of the proposed algorithm.

• Proceedings of the KIEE Conference
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• 1999.11b
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• pp.232-235
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• 1999

This paper presents a HNN(Hopfield Neural Network) model to solve the ORP(Optimal Routing Problem) in DSP(Distribution System Planning). This problem is generally formulated as a combinatorial optimization problem with various equality and inequality constraints. Precedent study[3] considered only fixed cert, but in this paper, we proposed the capability of optimization by fixed cost and variable cost. And suggested the corrected formulation of energy function for improving the characteristics of convergence. The proposed algorithm has been evaluated through the sample distribution planning problem and the simmulation results are presented.

• Proceedings of the KSME Conference
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• 2000.11a
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• pp.381-386
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• 2000

Simple spring-damper-mass models have been widely used to understand whole-body vertical biodynamic response characteristics of the seated vehicle driver. However, most previous models have not considered about the non-rigid masses(wobbling masses). A simple mechanical model of seated human body developed in this study included the torso represented by a rigid and a wobbling mass. Within the 0.5-20Hz frequency range and for excitation amplitudes maintained below $5ms^{-2}$, this 4-degree-of-freedom driver model is proposed to satisfy the measured vertical vibration response characteristics defined from a synthesis of published data for subjects seated erect without backrest support. The parameters are identified by using the combinatorial optimization technique, simulated annealing method. The model response was found to be provided a closer agreement with the response characteristics than previously published models.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1996.10a
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• pp.253-256
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• 1996

Rainfall is one of the major and complicated elements of hydrologic system. Accurate prediction of rainfall is very important to mitigate storm damage. The neural network is a good model to be applied for the classification problem, large combinatorial optimization and nonlinear mapping. In this dissertation, rainfall predictions by the neural network theory were presented. A multi-layer neural network was constructed. The network learned continuous-valued input and output data. The network was used to predict rainfall. The online, multivariate, short term rainfall prediction is possible by means of the developed model. A multidimensional rainfall generation model is applied to Seoul metropolitan area in order to generate the 10-minute rainfall. Application of neural network to the generated rainfall shows good prediction. Also application of neural network to 1-hour real data in Seoul metropolitan area shows slightly good predictions.

• IE interfaces
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• v.15 no.2
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• pp.189-198
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• 2002

Simulated Annealing(SA) approach has been successfully applied to the combinatorial optimization problems with NP-hard complexity. To apply an SA algorithm to specific problems, generic parameters as well as problem-specific parameters must be determined. To overcome the embedded nature of SA, long computational time, some studies suggested the parameter design methods of determining SA related parameters. In this study, we propose a new parameter design approach based on robust design method. To show the effectiveness of the proposed method, the extensive computation experiments are conducted on the mixed-model sequencing problems.

• Industrial Engineering and Management Systems
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• v.11 no.1
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• pp.18-25
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• 2012

IChinese postman problem is one of the classical combinatorial optimization problems with many applications. However, in application, some uncertain factors are frequently encountered. This paper employs uncertain programming to deal with Chinese postman problem with uncertain weight Within the framework of uncertainty theory, the concepts of expected shortest route, ${\alpha}$-shortest route, and distribution shortest route are proposed. After that, expected shortest model, and ${\alpha}$-shortest model are constructed. Taking advantage of properties of uncertainty theory, these models can be transf-ormed into their corresponding deterministic forms, which can be solved by classical algorithm..

• Journal of Korean Society of Water and Wastewater
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• v.27 no.4
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• pp.413-428
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• 2013

In this study, Ant Colony Algorithm(ACO) was used for optimal model. ACO which are metaheuristic algorithm for combinatorial optimization problem are inspired by the fact that ants are able to find the shortest route between their nest and food source. For applying the model to water distribution systems, pipes, tanks(reservoirs), pump construction and pump operation cost were considered as object function and pressure at each node and reservoir level were considered as constraints. Modified model from Ostfeld and Tubaltzev(2008) was verified by applying 2-Looped, Hanoi and Ostfeld's networks. And sensitivity analysis about ant number, number of ants in a best group and pheromone decrease rate was accomplished. After the verification, it was applied to real water network from S water treatment plant. As a result of the analysis, in the Two-looped network, the best design cost was found to $419,000 and in the Hanoi network, the best design cost was calculated to $6,164,384, and in the Ostfeld's network, the best design cost was found to $3,525,096. These are almost equal or better result compared with previous researches. Last, the cost of optimal design for real network, was found for 66 billion dollar that is 8.8 % lower than before. In addition, optimal diameter for aged pipes was found in this study and the 5 of 8 aged pipes were changed the diameter. Through this result, pipe construction cost reduction was found to 11 percent lower than before. And to conclusion, The least cost design model on water distribution system was developed and verified successfully in this study and it will be very useful not only optimal pipe change plan but optimization plan for whole water distribution system.

• 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.