• 한국경영과학회지
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• 제27권2호
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• pp.153-171
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• 2002

In this paper, we present an efficient pricing strategy, the pivot and probe Algorithm for Network Flow Problems(PAPANET), specifically for solving capacitated, linear network flow problem (NPs). The PAPANET begins with an initial relaxed network problem(RNP), consisting of all the nodes and initial candidate arcs(possibly a few least cost arcs form the original problem and a set of all the artificial and slack arcs). After an initial solution to the RNP is derived by pivoting, the PROBE procedure identifies a set of most violated arcs from the noncandidate arcs that are not considered to be in the current RNP, and adds them to the RNP. The procedure also discards a set of least favorable, zero flow, nonbasic arcs from the RNP. The new RNP is solved to optimality and the procedure continues until all of the dual constraints of the noncandidate arcs are satisfied by the dual solution to the RNP. The PAPANET effectively reduces the problem size, time per pivot, and solution CPU time by eliminating noncandidate arcs. Computational tests on randomly generated problems indicate that PAPANET achieves and average savings of 50-80% of the solution CPU time of that of a comparable standard network simplex implementation.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.175-178
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• 2003

In recent years, several researchers have presented the extensive research reports on network optimization problems. In our real life applications, many important network problems are typically formulated as a Maximum flow model (MXF) or a Minimum Cost flow model (MCF). In this paper, we propose a Genetic Algorithm (GA) approach used a priority-based chromosome for solving the bicriteria network optimization problem including MXF and MCF models(MXF/MCF).

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 하계종합학술대회 논문집(2)
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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.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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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.

• 경영과학
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• 제21권1호
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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.

• 산업공학
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• 제10권3호
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• pp.179-187
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• 1997

The efficiency of material flow systems in terms of optimal network flow and minimum cost flow has always been an important design and operational goal in material handling and distribution system. In this research, an attempt was made to develop a new algorithm and the model to solve a stochastic material flow network with bidirectional and uncertain flows. A stochastic material flow network with bidirectional flows can be considered from a finite set with unknown demand probabilities of each node. This problem can be formulated as a special case of a two-stage linear programming problem which can be converted into an equivalent linear program. To find the optimal solution of proposed stochastic material flow network, some terminologies and algorithms together with theories are developed based on the partitioning and subgradient techniques. A computer program applying the proposed method was developed and was applied to various problems.

• 설비공학논문집
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• 제18권8호
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• pp.635-640
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• 2006

An optimizer has been applied for the optimal design of pipe diameters in the pipe flow network problems. Pipe network flow analysis, which is developed separately, is performed within the interface for the optimization algorithm. A pipe network is chosen for the test, and optimizer GenOpt is applied with Holder-Mead-O'Niell's simplex algorithm after solving the network flow problem by the Newton-Raphson method. As a result, optimally do-signed pipe diameters are successfully obtained which minimize the total design cost. Design cost of pipe flow network can be considered as the sum of pipe installation cost and pump operation cost. In this study, a practical and efficient solution method for the pipe network optimization is presented. Test system is solved for the demonstration of the present optimization technique.

• 한국시뮬레이션학회:학술대회논문집
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• 한국시뮬레이션학회 1998년도 The Korea Society for Simulation 98 춘계학술대회 논문집
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• pp.11-16
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• 1998

The classical algorithm for solving liner network flow problems are primal cost improvement method, including simplex method, which iteratively improve the primal cost by moving flow around simple cycles, which iteratively improve the dual cost by changing the prices of a subset of nodes by equal amounts. Typical iteration/shortest path algorithm is used to improve flow problem of liner network structure. In this paper we stdudied about the implemental method of shortest path which is a practical computational aspects. This method can minimize the best neighbor node and also implement the typical iteration which is $\varepsilon$-CS satisfaction using the auction algorithm of linear network flow problem

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권2호
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• pp.733-750
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• 2019

Software Defined Networking (SDN) is a new network paradigm, allowing administrators to manage networks through central controllers by separating control plane from data plane. So, one or more controllers must locate outside switches. However, this separation may cause delay problems between controllers and switches. In this paper, we therefore propose a Priority-based Scheduling policy for OpenFlow (PSO) to reduce the delay of some significant traffic. Our PSO is based on packet prioritization mechanisms in both OpenFlow switches and controllers. In addition, we have prototyped and experimented on PSO using a network simulator (ns-3). From the experimental results, PSO has demonstrated low delay for targeted traffic in the out-of-brand control network. The targeted traffic can acquire forwarding rules with lower delay under network congestion in control links (with normalized load > 0.8), comparing to traditional OpenFlow. Furthermore, PSO is helpful in the in-band control network to prioritize OpenFlow messages over data packets.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권10호
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• pp.4902-4932
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• 2016

The popularity of network virtualization has recently regained considerable momentum because of the emergence of OpenFlow technology. It is essentially decouples a data plane from a control plane and promotes hardware programmability. Subsequently, OpenFlow facilitates the implementation of network virtualization. This study aims to provide an overview of different approaches to create a virtual network using OpenFlow technology. The paper also presents the OpenFlow components to compare conventional network architecture with OpenFlow network architecture, particularly in terms of the virtualization. A thematic OpenFlow network virtualization taxonomy is devised to categorize network virtualization approaches. Several testbeds that support OpenFlow network virtualization are discussed with case studies to show the capabilities of OpenFlow virtualization. Moreover, the advantages of popular OpenFlow controllers that are designed to enhance network virtualization is compared and analyzed. Finally, we present key research challenges that mainly focus on security, scalability, reliability, isolation, and monitoring in the OpenFlow virtual environment. Numerous potential directions to tackle the problems related to OpenFlow network virtualization are likewise discussed.