• 대한교통학회지
• /
• 제31권6호
• /
• pp.12-21
• /
• 2013

관광지역 내 궤도교통수단 요금은 사업 타당성 판단의 중요한 변수가 되는 요소이다. 기존 운영자 위주의 요금 결정에서 벗어나, 이용자 측면까지 동시에 고려된 요금을 산출함으로써 운영자와 이용자를 동시에 만족시키는데 본 연구의 목적이 있다. 본 연구의 대상은 인천광역시 중구 월미도 일대를 순환하는 월미은하레일이다. 본 연구에서는 요금의 적정 범위를 판단하기 위해 운영자 비용과 이용자 비용을 최적화하는 모형을 구축하였다. 최적화된 모형을 활용하여 각 변수의 값을 산출한 결과, 정류장 간격은 0.532km, 운행 간격은 0.206시, 정류장 수는 12개소, 운행 대수는 3대로 도출되었다. 이렇게 도출된 변수들을 활용하여 이용자가 지불해야하는 최소요금과 운영자가 징수해야 하는 최소요금을 산출하고, 이를 근거로 요금의 적정범위를 분석한 결과 최소 1,261원에서 최대 5,063원인 것으로 분석되었다. 관광교통수단의 경우 정류장 자체가 관광지 내에 위치하므로 모형 적용시 접근거리 감소폭이 매우 적어 접근비용의 변화폭이 미미하다는 점을 확인할 수 있었다.

• 상하수도학회지
• /
• 제29권3호
• /
• pp.293-303
• /
• 2015

Optimal design of the water supply pipe network aims to minimize construction cost while satisfying the required hydraulic constraints such as the minimum and maximum pressures, and velocity. Since considering one single design factor (i.e., cost) is very vulnerable for including future conditions and cannot satisfy operator's needs, various design factors should be considered. Hence, this study presents three kinds of design factors (i.e., minimizing construction cost, maximizing reliability, and surplus head) to perform multi-objective optimization design. Harmony Search (HS) Algorithm is used as an optimization technique. As well-known benchmark networks, Hanoi network and Gyeonggi-do P city real world network are used to verify the applicability of the proposed model. In addition, the proposed multi-objective model is also applied to a real water distribution networks and the optimization results were statistically analyzed. The results of the optimal design for the benchmark and real networks indicated much better performance compared to those of existing designs and the other approach (i.e., Genetic Algorithm) in terms of cost and reliability, cost, and surplus head. As a result, this study is expected to contribute for the efficient design of water distribution networks.

• 경영과학
• /
• 제21권1호
• /
• pp.77-86
• /
• 2004

In this paper, we present a methodology for solving the multicommodity network flow problems using interior point methods. In our method, the minimum cost network flow problem extracted from the given multicommodity network flow problem is solved by primal-dual barrier method in which normal equations are solved partially using preconditioned conjugate gradient method. Based on the solution of the minimum cost network flow problem, a warm-start point is obtained from which Castro's specialized interior point method for multicommodity network flow problem starts. In the computational experiments, the effectiveness of our methodology is shown.

• 한국철도학회:학술대회논문집
• /
• 한국철도학회 2004년도 춘계학술대회 논문집
• /
• pp.507-513
• /
• 2004

In the railway system, transportation plan corresponds to a m aster plan for transport services. This service plan must be constructed to minimize operational cost or maximize revenue considering transportation demands and resource capacities in the railway operation company, and it includes several sub-planning activities such as train operation frequency plan, train (schedule) plan, train capacity assignment plan, and rolling stock requirement plan. In these sub- planning processes, train can be con side red as a product for providing customer services, and customer demands and operational advantages must be considered. In this paper, we present an effect estimation system for the train capacity pattern in a train schedule, and the effect of capacity pattern can be expressed as minimum spilled demand, minimum train service cost, and maximum train revenue or profit.

• 한국경영과학회:학술대회논문집
• /
• 대한산업공학회/한국경영과학회 2006년도 춘계공동학술대회 논문집
• /
• pp.25-32
• /
• 2006

Given a schedule of train to be routed by a Railway Stock, Railway Stock Routing Problem determine a sequence of train while satisfying turnaround time and maintenance restrictions. The objective is to minimize the Railway Stock during a week and each day simultaneously. And we prove that Railway Stock Routing Problem with maintenance restrictions is NP-hard. In this paper, we present two stage approaches that solve the Railway Stock Routing Problem in a reasonable time. In first stage we relax maintenance restrictions and formulate as a Min-cost-flow problem. Then, in the second stage, we attempt to satisfy maintenance restrictions using ours heuristic algorithm. We show the computational result of applying to an actual train schedule data.

• 제어로봇시스템학회논문지
• /
• 제13권1호
• /
• pp.52-57
• /
• 2007

In this paper we proposed multi-directional matching windows combined by multi-dimensional feature vector matching, which uses not only intensity values but also multiple feature values, such as variance, first and second derivative of pixels. Multi-dimensional feature vector matching has the advantage of compensating the drawbacks of area-based stereo matching using one feature value, such as intensity. We define matching cost of a pixel by the minimum value among eight multi-dimensional feature vector distances of the pixels expanded in eight directions having the interval of 45 degrees. As best stereo matches, we determine the two points with the minimum matching cost within the disparity range. In the experiment we used aerial imagery and IKONOS satellite imagery and obtained more accurate matching results than that of conventional matching method.

• Journal of Communications and Networks
• /
• 제12권1호
• /
• pp.86-94
• /
• 2010

In this paper, we present a decentralized algorithm to find minimum cost quality of service (QoS) flow subgraphs in network coded multicast schemes. The main objective is to find minimum cost subgraphs that also satisfy user-specified QoS constraints, specifically with respect to rate and delay demands. We consider networks with multiple multicast sessions. Although earlier network coding algorithms in this area have demonstrated performance improvements in terms of QoS parameters, the proposed QoS network coding approach provides a framework that guarantees QoS constraints are actually met over the network.

• 한국컴퓨터정보학회논문지
• /
• 제20권12호
• /
• pp.75-82
• /
• 2015

Generally, the optimal solution of assignment problem can be obtained by Hungarian algorithm of two-sided optimization with time complexity $O(n^4)$. This paper suggests one-sided optimal assignment and swap optimization algorithm with time complexity $O(n^2)$ can be achieve the goal of two-sided optimization. This algorithm selects the minimum cost for each row, and reassigns over-assigned to under-assigned cell. Next, that verifies the existence of swap optimization candidates, and swap optimizes with ${\kappa}-opt({\kappa}=2,3)$. For 27 experimental data, the swap-optimization performs only 22% of data, and 78% of data can be get the two-sided optimal result through one-sided optimal result. Also, that can be improves on the solution of best known solution for partial problems.

• 디지털산업정보학회논문지
• /
• 제5권4호
• /
• pp.117-126
• /
• 2009

The recent interest in sensor networks has led to a number of routing schemes that use the limited resources available at sensor nodes more efficiently. These schemes typically try to find the minimum energy path to optimize energy usage at a node. Some schemes, however, are prone to unbalance of the traffic and energy. To solve this problem, we propose a novel solution: a gradient-field approach which takes account of the minimum cost data delivery, energy consumption balancing, and traffic equalization. We also modify the backoff-based cost field setup algorithm to establish our gradient-field based sensor network and give the algorithm. Simulation results show that the overhead of routing establishment obtained by our algorithm is much less than the one obtained by Flooding. What's more, our approach guarantees the basic Quality of Service (QoS) without extra spending.

• 대한전자공학회:학술대회논문집
• /
• 대한전자공학회 2000년도 ITC-CSCC -1
• /
• pp.493-496
• /
• 2000

We study the problem of designing at minimum cost a two-connected network topology such that the shortest cycle to which each edge belongs does not exceed a given maximum number of hops. This problem is considered as part of network planning and arises in the design of backbone networks. We propose a genetic algorithm approach that uses a solution representation, in which the connectivity and ring constraints can be easily encoded. We also propose a crossover operator that ensures a generated solution is feasible. By doing so, the checking of constraints is avoided and no repair mechanism is required. We carry out experimental evaluations to investigate the solution representation issues and GA operators for the network design problem.