• 대한산업공학회지
• /
• 제34권2호
• /
• pp.181-189
• /
• 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.

• 부동산연구
• /
• 제28권1호
• /
• pp.23-37
• /
• 2018

유전 알고리즘(Genetic Algorithm) 과 분단탐색법(Branch & Bound Method)은 문재인 정부의 핵심적인 부동산 정책인 도시재생 뉴딜사업에서 대상지역을 선정할 때 제한된 예산범위 내에서 사업의 효과가 큰 사업지구들을 지역균형을 고려하여 합리적으로 선정하는 유용한 방법론이다. 2017년 도시재생 뉴딜 시범사업에서는 각 광역지자체가 최대 3곳의 사업지구를 신청할 수 있고, 국토교통부는 이 중에서 중심시가지형 13곳, 경제기반형 2곳을 선정하며, 공공기관제안형 도시재생사업을 별도로 광역지자체에서 신청받아 10곳을 선정할 계획이다. 그런데 사업의 효과만을 기준으로 사업지구를 선정하면 지역균형발전에 부정적인 영향(1곳도 선정되지 않는 지자체 발생)을 미칠 수 있으므로 이에 대한 고려가 필요하다. 그러므로 본 연구에서는 최적화 모형을 구성하기 위해 유전 알고리즘 및 분단탐색법을 응용하여 지역균형발전 조건을 만족하면서 사업효과를 극대화하는 최적 사업지구조합을 도출한다. 이러한 방법론은 경우의 수가 대단히 많아 직관적으로 해결하기 불가능한 조합 최적화의 문제를 해결하는데 매우 적합하며, 부동산학뿐만 아니라 다양한 분야에 응용할 수 있는 방법론임을 2017년 도시재생 뉴딜 시범사업 선정사례를 통해 알 수 있었다. 향후 중앙정부가 특정목적의 제한된 예산을 각 지자체들에 배분하는 사례에서 이 방법론을 적용한 결과가 합리적인 기준이 될 것으로 기대한다.

• 대한기계학회논문집
• /
• 제19권8호
• /
• pp.1854-1868
• /
• 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.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 1999년도 추계학술대회 논문집 학회본부 A
• /
• pp.232-235
• /
• 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.

• 대한기계학회:학술대회논문집
• /
• 대한기계학회 2000년도 추계학술대회논문집A
• /
• pp.381-386
• /
• 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.

• 한국지능시스템학회:학술대회논문집
• /
• 한국퍼지및지능시스템학회 1996년도 추계학술대회 학술발표 논문집
• /
• pp.253-256
• /
• 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.

• 산업공학
• /
• 제15권2호
• /
• pp.189-198
• /
• 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
• /
• 제11권1호
• /
• pp.18-25
• /
• 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..

• 상하수도학회지
• /
• 제27권4호
• /
• pp.413-428
• /
• 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.

• 물과 미래
• /
• 제29권4호
• /
• pp.109-118
• /
• 1996

신경망이론은 분산기억성질과 병렬국소처리를 수행하는 뇌의 활동을 이론화한 수학모형이다. 이러한 신경망이론의 장점은 분류문제, 대규모로 결합된 최적화문제, 비선형 사상문제 등에서 잘 나타나므로, 이 점을 이용하여 복잡한 강우의 예측을 시도하였다. 신경망이론을 적용하기 위해서 연속적인 값으로 표시되는 입력자료와 출력자료를 학습한 후 강우예측을 시행할 수 있는 다층신경망 모형을 구성하였다. 신경망이론에 의한 강우예측은 서울지역과 소양강유역의 1 시간 대위 강우자료에 적용하였다. 그 결과는 대체로 만족할 만하였다. 따라서 신경망이론은 양질의 자료가 충분히 확보될 경우복잡한 강우현상을 잘 예측할 것으로 기대된다.