• Journal of the military operations research society of Korea
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• v.25 no.2
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• pp.84-96
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• 1999

The purpose of this paper is to find the most vital arc in the minimum cost flow problem. The most vital arc is the arc whose removal results in the greatest influence in the costs or the amount of demands in a given minimum cost flow network. This problem can be well applied to the conflict situations such as military logistics network or communications network. In this situation, network user wants to know which arcs are the most vital to him so that he can reinforce these arcs against attack, while interdictor wants to destroy these arcs which increase the distance of the shortest path most through the network. When one of arcs is removed from the network of the minimum cost flow problem, two kinds of situations can be occurred ; breaking feasibility and increasing cost. In case of breaking feasibility, the rank of arcs are determined using the amount of modified flow in a related network which is made of modifying the optimal alternative of the minimum cost flow problem. The rank of arcs with the increased costs are determined by using a method which finds the directed cycle with the minimum cost in a related network.

• Proceedings of the IEEK Conference
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• 2000.06b
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• pp.213-216
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• 2000

Minimum-cost linear network flow problems could be transformed with equal to assignment problems. Traditional method to solve the linear network flow problems are improved source-cost by transform the simple cycle flow. Auction algorithm could be applied to same element using the initial target price and dispersion calculation. Also, each elements are obtained by $\varepsilon$-relaxation methods. In this paper we proposed; 1)minimum-cost flow problem, 2)minimum-cost flow problem by the mathematical equivalent and 3) extraction $\varepsilon$-relaxation & expand transfer problem with minimum-cost flow. It can be applicant to PCB design by above mentioned.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.33 no.1
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• pp.9-16
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• 1984

This paper describes the minimum cost expansion planning which is based on the economical aspect under the various conditions on the power system expansion planning. It presents not only linear cost characteristics analysis but also stepwise cost characteristics analysis which satisfies practical condition in the power system. The latter analysis must be handled by integer programming (IP), because the relation between the cost and the capacity has stepwise characteristics. In order to proceed the latter analysis, the solving procedure is illustrated in detais by using branch and bound method which includes the network flow theory and maximum flow-minimum cut theorem.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.43
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• pp.67-79
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• 1997

In this paper we develop the integrated software that can compare algorithms of the minimum cost flow problem using PC. The chosen algorithms are the network simplex method, dual network simplex method, and out-of-kilter method, which methods correspond to primal, dual, and primal-dual approach respectively. We also present the improved methods obtaining the initial solution to increase the efficiency of algorithms, and experiment results shown the difference between the entering(dropping) selection rules.

• Korean Management Science Review
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• v.21 no.1
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• pp.77-86
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• 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.

• Smart Media Journal
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• v.12 no.9
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• pp.72-80
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• 2023

This paper presents a design and analyzes the performance of a hospital assignment and reassignment scheme for emergency rescue services based on minimum cost maximum flow algorithm. It consists of flow graph building, link capacity updating, and allocation discovering steps. The efficiency of the algorithm makes it possible to reallocate hospitals even in case of dynamic changes in the number of patients or hospitals. The performance measurement result obtained from a prototype implementation shows that the proposed scheme can reduce the transport time requirement miss by up to 24%.

• Journal of the Korean Operations Research and Management Science Society
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• v.25 no.4
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• pp.15-25
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• 2000

In this paper, we introduce a point-to-multipoint minimum cost flow problem with convex and demand splitting. A source node transmits the traffic along the tree that includes members of the point-to-multipoint connection. The traffic is replicated by the nodes only at branch points of the tree. In order to minimize the sum of arc costs, we assume that the traffic demand can be splitted and transmitted to destination nodes along different trees. If arc cost is linear, the problem would be a Steiner tree problem in networks eve though demand splitting is permitted. The problem would be applied in transmitting large volume of traffic from a serve to clients in Internet environments. Optimality conditions of the problem are presented in terms of fair tree routing. The proposed algorithm is a finite terminating algorithm for $\varepsilon$-optimal solution. convergence of the algorithm is obtained under monotonic condition and strict convexity of the cost function. Computational experiences are included.

• Journal of the Korean Operations Research and Management Science Society
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• v.14 no.2
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• pp.53-66
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• 1989

The Public Vehicle Routing Problem (PVRP) is to find the minimum total cost routes of M or less Public-Vehicles to traverse the required arcs(streets) at least once, and return to their starting depot on a directed network. In this paper, first, a mathematical model is formulated as minimal cost flow model with illegal subtour elimination constraints, and with the fixed cost and routing cost as an objective function. Second, an efficient branch and bound algorithm is developed to obtain an exact solution. A subproblem in this method is a minimal cost flow problem relaxing illegal subtour elimination constraints. The branching strategy is a variable dichotomy method according to the entering nonrequired arcs which are candidates to eneter into an illegal subtour. To accelerate the fathoming process, a tighter lower bound of a candidate subproblem is calculated by using a minimum reduced coast of the entering nonrequired arcs. Computational results based on randomly generated networks report that the developed algorithm is efficient.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.195-204
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• 2003

Network optimization is being increasingly important and fundamental issue in the fields such as engineering, computer science, operations research, transportation, telecommunication, decision support systems, manufacturing, and airline scheduling. Networks provide a useful way to modeling real world problems and are extensively used in practice. Many real world applications impose on more complex issues, such as, complex structure, complex constraints, and multiple objects to be handled simultaneously and make the problem intractable to the traditional approaches. Recent advances in evolutionary computation have made it possible to solve such practical network optimization problems. The invited talk introduces a thorough treatment of evolutionary approaches, i.e., hybrid genetic algorithms approach to network optimization problems, such as, fixed charge transportation problem, minimum cost and maximum flow problem, minimum spanning tree problem, multiple project scheduling problems, scheduling problem in FMS.

• International Journal of Contents
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• v.15 no.4
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• pp.8-15
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• 2019

This paper presents a solution of the 'Quick, Draw! Doodle Recognition Challenge' hosted by Google. Doodles are drawings comprised of concrete representational meaning or abstract lines creatively expressed by individuals. In this challenge, a doodle is presented as a sequence of sketches. From the view of at the sketch level, to learn the pattern of strokes representing a doodle, we propose a sequential model stacked with multiple convolution layers and Long Short-Term Memory (LSTM) cells following the attention mechanism [15]. From the view at the image level, we use multiple models pre-trained on ImageNet to recognize the doodle. Finally, an ensemble and a post-processing method using the minimum cost flow algorithm are introduced to combine multiple models in achieving better results. In this challenge, our solutions garnered 11th place among 1,316 teams. Our performance was 0.95037 MAP@3, only 0.4% lower than the winner. It demonstrates that our method is very competitive. The source code for this competition is published at: https://github.com/ngxbac/Kaggle-QuickDraw.