Algorithms for network piecewise-linear programs: A comparative study

Algorithms for network piecewise-linear programs: A comparative study

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Article ID: iaor19991477
Country: Netherlands
Volume: 97
Issue: 1
Start Page Number: 183
End Page Number: 199
Publication Date: Feb 1997
Journal: European Journal of Operational Research
Authors: , , , ,
Abstract:

Piecewise-Linear Programming (PLP) is an important area of Mathematical Programming and concerns the minimisation of a convex separable piecewise-linear objective function, subject to linear constraints. In this paper a subarea of PLP called Network Piecewise-Linear Programming (NPLP) is explored. The paper presents four specialised algorithms for NPLP: (Strongly Feasible) Primal Simplex, Dual Method, Out-of-Kilter and (Strongly Polynomial) Cost-Scaling, and their relative efficiency is studied. A statistically designed experiment is used to perform a computational comparison of the algorithms. The response variable observed in the experiment is the CPU time to solve randomly generated network piecewise-linear problems classified according to problem class (Transportation, Transshipment and Circulation), problem size, extent of capacitation, and number of breakpoints per arc. Results and conclusions on performance of the algorithms are reported.

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