This paper addresses a stochastic-#ow network in which each arc or node has several capacities and may
fail. Given the demand d, we try to evaluate the system reliability that the maximum #ow of the network is
not less than d. A simple algorithm is proposed "rstly to generate all lower boundary points for d, and then
the system reliability can be calculated in terms of such points. One computer example is shown to illustrate
the solution procedure.
This paper addresses a stochastic-#ow network in which each arc or node has several capacities and may
fail. Given the demand d, we try to evaluate the system reliability that the maximum #ow of the network is
not less than d. A simple algorithm is proposed "rstly to generate all lower boundary points for d, and then
the system reliability can be calculated in terms of such points. One computer example is shown to illustrate
the solution procedure.
This paper addresses a stochastic-#ow network in which each arc or node has several capacities and may
fail. Given the demand d, we try to evaluate the system reliability that the maximum #ow of the network is
not less than d. A simple algorithm is proposed "rstly to generate all lower boundary points for d, and then
the system reliability can be calculated in terms of such points. One computer example is shown to illustrate
the solution procedure.
This paper addresses a stochastic-#ow network in which each arc or node has several capacities and may
fail. Given the demand d, we try to evaluate the system reliability that the maximum #ow of the network is
not less than d. A simple algorithm is proposed "rstly to generate all lower boundary points for d, and then
the system reliability can be calculated in terms of such points. One computer example is shown to illustrate
the solution procedure.
This program is free software you can redistribute it and/or
modify it under the terms of the GNU General Public License
as published by the Free Software Foundation either version 2
of the License, or (at your option) any later version.
Samples are organized by chapter, and then by "application" or example name. You should open a project in Visual Studio .NET through the .sln (solution) file.
Note that Visual Studio .NET automatically creates various temporary and debugging files in the obj and bin sub-directory for each project. The actual uncompiled code is only the .vb files that are contained in the root project directory.
The data files included are .MAT or *.dat (ASCII)files. The m-files and the
data may be distributed, provided that the source is acknowledged in any
publication and the data are not sold. Since this software is being distributed
free of charge, the authors are not offering any technical support. Students who
have any questions or difficulties using this software, or require the
additional functions from the Signal Processing Toolbox should contact their
professor.
