A mixed integer program for partitioning graphs with supply and demand emphasizing sparse graphs

Raka Jovanovic, Stefan Voß

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

The focus of this paper is on finding optimal solutions for the problem of maximal partitioning of graphs with supply and demand (MPGSD) for arbitrary graphs. A mixed integer programming (MIP) model is developed for the problem of interest. We also present some specific constraints that can be used in the case of tree graphs. With the goal of lowering the computational cost for solving the underlying model, a preprocessing stage is included. It is used to produce additional constraints based on shortest paths in the graph. With the aim of exploring the effectiveness of the proposed MIP formulation we have performed computational experiments for general graphs and trees. The main objective of the tests is to observe the properties and sizes of supply/demand graphs that can be solved to optimality using the proposed approach in reasonable time. The conducted computational experiments have shown that the proposed method is especially suitable for sparse graphs.

Original languageEnglish
JournalOptimization Letters
DOIs
Publication statusAccepted/In press - 4 Nov 2015

Fingerprint

Mixed Integer Program
Graph Partitioning
Sparse Graphs
Graph in graph theory
Mixed Integer Programming
Computational Experiments
Shortest path
Programming Model
Preprocessing
Demand
Computational Cost
Partitioning
Optimality
Optimal Solution
Formulation
Arbitrary

Keywords

  • Demand vertex
  • Graph partitioning
  • Mixed integer programming
  • Supply vertex

ASJC Scopus subject areas

  • Control and Optimization

Cite this

A mixed integer program for partitioning graphs with supply and demand emphasizing sparse graphs. / Jovanovic, Raka; Voß, Stefan.

In: Optimization Letters, 04.11.2015.

Research output: Contribution to journalArticle

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