Treffer: Two-phase algorithms for the parametric shortest path problem

Title:
Two-phase algorithms for the parametric shortest path problem
Contributors:
Centrum voor Wiskunde en Informatica (CWI), Centrum Wiskunde & Informatica (CWI)-Netherlands Organisation for Scientific Research, Department of Computer Science [Haifa], Ǧāmiʿat͏̈ Hayfā = University of Haifa, Centre for Discrete Mathematics and its Applications, University of Warwick [Coventry], Department of Mathematics [Haïfa], Inria Nancy Grand Est & Loria, Jean-Yves Marion and Thomas Schwentick
Source:
27th International Symposium on Theoretical Aspects of Computer Science - STACS 2010. :167-178
Publisher Information:
CCSD, 2010.
Publication Year:
2010
Collection:
collection:STACS2010
Subject Geographic:
Original Identifier:
HAL:
Document Type:
Konferenz conferenceObject<br />Conference papers
Language:
English
Rights:
info:eu-repo/semantics/OpenAccess
Accession Number:
edshal.inria.00455816v1
Database:
HAL

Weitere Informationen

A {\em parametric weighted graph} is a graph whose edges are labeled with continuous real functions of a single common variable. For any instantiation of the variable, one obtains a standard edge-weighted graph. Parametric weighted graph problems are generalizations of weighted graph problems, and arise in various natural scenarios. Parametric weighted graph algorithms consist of two phases. A {\em preprocessing phase} whose input is a parametric weighted graph, and whose output is a data structure, the advice, that is later used by the {\em instantiation phase}, where a specific value for the variable is given. The instantiation phase outputs the solution to the (standard) weighted graph problem that arises from the instantiation. The goal is to have the running time of the instantiation phase supersede the running time of any algorithm that solves the weighted graph problem from scratch, by taking advantage of the advice. In this paper we construct several parametric algorithms for the shortest path problem. For the case of linear function weights we present an algorithm for the single source shortest path problem.