Solving resource constrained shortest path problems with LP-based methods

Markó Horváth, T. Kis

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

In the resource constrained shortest path problem (RCSPP) there is a directed graph along with a source node and a destination node, and each arc has a cost and a vector of weights specifying its requirements from a set of resource types with finite capacities. A minimum cost source-destination directed path is sought such that the total consumption of the arcs from each resource type does not exceed the capacity of the resource. In this paper we investigate LP-based branch-and-bound methods and introduce new cutting planes, separation procedures, variable fixing, and primal heuristic methods for solving RCSPP to optimality. We provide detailed computational experiments, and a comparison to other methods in the literature.

Original languageEnglish
Pages (from-to)150-164
Number of pages15
JournalComputers and Operations Research
Volume73
DOIs
Publication statusPublished - Sep 1 2016

Fingerprint

Shortest Path Problem
Branch and bound method
Resources
Heuristic methods
Directed graphs
Costs
Arc of a curve
Finite Capacity
Branch and Bound Method
Cutting Planes
Heuristic Method
Vertex of a graph
Computational Experiments
Directed Graph
Experiments
Optimality
Exceed
Shortest path
Path
Requirements

Keywords

  • Branch-and-cut
  • Combinatorial optimization
  • Integer programming
  • Primal heuristics
  • Resource constrained shortest path

ASJC Scopus subject areas

  • Computer Science(all)
  • Management Science and Operations Research
  • Modelling and Simulation

Cite this

Solving resource constrained shortest path problems with LP-based methods. / Horváth, Markó; Kis, T.

In: Computers and Operations Research, Vol. 73, 01.09.2016, p. 150-164.

Research output: Contribution to journalArticle

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