• Journal of the military operations research society of Korea
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• v.18 no.2
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• pp.151-166
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• 1992

In this paper, we define a problem finding a simple path that maximizes the sum of the satisfied Origin-Destination (O-D) flows between nodes covered by that path as a Maximum O-D Flow Path Problem(MODEP). We established a formulation and suggested a method finding MODEP in a directed network. The method utilizes the constraint relaxation technique and the Dual All Integer Algorithm.

• Journal of the Korean Operations Research and Management Science Society
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• v.16 no.1
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• pp.1-12
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• 1991

This paper studies an optimal algorithm for the Maximum Origin-Destination Flor Path (MODFP) in an acyclic transportation network. We define a Pseudo-Flow each are so that it can give an upper bound to the total flow of a given path. And using the K-th Shortest Path algorithm we obtain upper bound of MODF which is decreasing as the number of searched path grows. Computational Complexity of optimal algorithm is O(K + m) $n_{2}$), K being the total number of searched path. We proved that the problem complexity of finding MODFP in an acyclic network is NP-hard, showing that the-satisfiability problem can be polynomialy reduced to this problem. And we estimated the average of the number K as being (m/n)$^{1,08}$ Exp (0.00689gm) from the computational experiments.

• Journal of the Korean Operations Research and Management Science Society
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• v.20 no.3
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• pp.31-41
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• 1995

The maximum Origin-Destination Flow Path Problem (MODFP) in an Acyclic Network has known as NP-hard. K. S. Sung has suggested on Optimal Algorithm for MODFP based on the Pseudo flo or arc and the K-th shortest path algorithm. When we try to solve MODFP problem by general Branch and Bound Method (BBM), the upper and lower bounds of subproblems are so weak that the BBM become very inefficient. Here we utilized the Pseudo flow of arc' for the tight bounds of subproblems so that it can produce an efficient BBM for MODFP problem.

• Journal of Navigation and Port Research
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• v.39 no.1
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• pp.61-67
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• 2015

Inland transport becomes more and more important in connecting ports with inland. Therefore, studying on cargo flow from ports to regions has been active in progress by many researchers. However current statistical data of freight flow from origin locations to destination locations does not reflect the exact characteristics of freight flow. Also, they also do not reflect the characteristics of multimodal transport system in which cargos go through intermediate locations such as logistics center or inland container depot. In growing up the emergent need of rebuilding statistical data for freight flow from origin locations to destination locations, this paper will propose a freight flow model with logistics center and it will be verified by genetic algorithm through the simulation scenarios.

• Journal of Korean Institute of Industrial Engineers
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• v.16 no.2
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• pp.91-98
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• 1990

This paper studies a heuristic method for the Maximum Origin-Destination Flow Path (MODFP) in an acyclic transportation network. We construct a mathematical formulation for finding the MODFP. Then by applying Benders' partitioning method, we generate two subproblems which should be solved in turn so that they may give an optimal solution. We solve one subproblem by an optimal seeking algorithm and the other by a hueristic method. so that, we finally obtain a good solution. The computational complexity of calculating the optimal solution of the first subproblem is 0(mn) and that of calculating the heuristic solution of the other subproblem is $0(n^2).$ From the computational experiments, we estimated the performance of the heuristic method as being 99.3% and the computing time relative to optimal algorithm as being 28.76%.

• Management Science and Financial Engineering
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• v.15 no.1
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• pp.51-69
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• 2009

A network model and a Genetic Algorithm (GA) is proposed to solve the simultaneous estimation of the trip distribution and traffic assignment from traffic counts in the congested networks in a logit-based Stochastic User Equilibrium (SUE). The model is formulated as a problem of minimizing a non-linear objective function with the linear constraints. In the model, the flow-conservation constraints are utilized to restrict the solution space and to force the link flows become consistent to the traffic counts. The objective of the model is to minimize the discrepancies between two sets of link flows. One is the set of link flows satisfying the constraints of flow-conservation, trip production from origin, trip attraction to destination and traffic counts at observed links. The other is the set of link flows those are estimated through the trip distribution and traffic assignment using the path flow estimator in the logit-based SUE. In the proposed GA, a chromosome is defined as a real vector representing a set of Origin-Destination Matrix (ODM), link flows and route-choice dispersion coefficient. Each chromosome is evaluated by the corresponding discrepancies. The population of the chromosome is evolved by the concurrent simplex crossover and random mutation. To maintain the feasibility of solutions, a bounded vector shipment technique is used during the crossover and mutation.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.6
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• pp.14-24
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• 2018

Pedestrian movement of passengers using smart card within stations can be divided into three types of activities - straight ride and alight, line transfer, and station transfer. Straight ride and alight is transfer activity for which the card terminal and embarking line are identical. In this case, straight ride occurs at the origin station and straight alight occurs at the destination station. Line transfer refers to activity in which the subway line embarked on by the passenger is different from that which is disembarked. Succinctly, line transfer is transfer at a middle station, rather than at origin or destination stations. Station transfer occurs when the card terminal line and embarking line are different. It appears when station transfer happens at the origin station as starting transfer, and at the destination station as destination transfer. In the case of Metropolitan smart card data, origin and destination station card terminal line number data is recorded, but subway line data does not exist. Consequently, transportation card data, as it exists, cannot adequately be used to analyze pedestrian movement as a whole in subway stations. This research uses the smart card data, with its constraints, to propose an analysis model for passenger pedestrian movement within subway stations. To achieve this, a path selection model is constructed, which links origin and destination stations, and then applied for analysis. Finally, a case study of the metropolitan subway is undertaken and pedestrian volume analyzed.

• Journal of the Korea Safety Management & Science
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• v.13 no.1
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• pp.127-131
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• 2011

Even if there are no causing factors such as car crash and road works, traffic congestion come from traffic growth on the road. In this case, estimation of traffic flow helps find the solution of traffic congestion problem. In this paper, we present a optimization model which used on traffic equilibrium problem and studied the problem of inverting shortest path sets for complex traffic system. And we also develop pivotal decomposition algorithm for reliability function of complex traffic system. Several examples are illustrated.

• The KIPS Transactions:PartD
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• v.19D no.2
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• pp.127-132
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• 2012

In the Seoul metropolitan bus network, it may be necessary for a bus passenger to pick up a parcel, which has been purchased through e-commerce, at his or her convenient bus stop on the way to home or office. The flow-capturing location-allocation model can be applied to select pickup points for such bus stops so that they maximize the captured passenger flows, where each passenger flow represents an origin-destination (O-D) pair of a passenger trip. In this paper, we propose a fast heuristic algorithm to select pickup points using a large O-D matrix, which has been extracted from five million transportation card transactions. The experimental results demonstrate the bus stops chosen as pickup points in terms of passenger flow and capture ratio, and illustrate the spatial distribution of the top 20 pickup points on a map.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.11a
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• pp.599-617
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• 2006

A network model and a Genetic Algorithm(GA) is proposed to solve the simultaneous estimation of the trip distribution and traffic assignment from traffic counts in the congested networks in a logit-based Stochastic User Equilibrium (SUE). The model is formulated as a problem of minimizing the non-linear objective functions with the linear constraints. In the model, the flow-conservation constraints of the network are utilized to restrict the solution space and to force the link flows meet the traffic counts. The objective of the model is to minimize the discrepancies between the link flows satisfying the constraints of flow-conservation, trip production from origin, trip attraction to destination and traffic counts at observed links and the link flows estimated through the traffic assignment using the path flow estimator in the legit-based SUE. In the proposed GA, a chromosome is defined as a vector representing a set of Origin-Destination Matrix (ODM), link flows and travel-cost coefficient. Each chromosome is evaluated from the corresponding discrepancy, and the population of the chromosome is evolved by the concurrent simplex crossover and random mutation. To maintain the feasibility of solutions, a bounded vector shipment is applied during the crossover and mutation.