DocumentCode
1867707
Title
Efficient models for special types of non-linear maximum flow problems
Author
Tvorogova, Marina
Author_Institution
Dept. of Comput. Sci., Tech. Univ. Braunschweig, Braunschweig, Germany
fYear
2013
fDate
8-11 Sept. 2013
Firstpage
409
Lastpage
416
Abstract
In this paper, we consider the maximum flow problem on networks with non-linear transfer functions. We consider special types of transfer functions, which are particularly relevant for applications. For concave transfer functions, we reduce the NL-flow problem to the generalized flow problem and solve it using a polynomial-time approximation scheme. For convex, s-shaped and monotonically growing piecewise linear (PWL) transfer functions (the latter can always be divided into s-shaped fragments), we present an equivalent network representation that allows us to build a MILP model with a better performance than if we were using standard MILP formulations of PWL functions. The latter requires additional variables and constraints to force the correct (depending on the amount of flow) linear segment of PWL functions to be taken. In our model, the correct segment in an s-shaped fragment is chosen automatically due to the network´s structure. For the case when transfer functions are non-linear, we provide an error estimation for the approximated solution.
Keywords
approximation theory; computational complexity; integer programming; linear programming; network theory (graphs); MILP model; NL-flow problem; PWL transfer functions; concave transfer functions; error estimation; nonlinear maximum flow problems; nonlinear transfer functions; piecewise linear transfer functions; polynomial-time approximation scheme; s-shaped fragment; Approximation methods; Computational modeling; Computer science; Optimization; Piecewise linear approximation; Standards; Transfer functions;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Science and Information Systems (FedCSIS), 2013 Federated Conference on
Conference_Location
Krako??w
Type
conf
Filename
6644032
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