English

Heuristic solutions to robust variants of the minimum-cost integer flow problem

Artificial Intelligence 2020-02-27 v1 Neural and Evolutionary Computing Optimization and Control

Abstract

This paper deals with robust optimization applied to network flows. Two robust variants of the minimum-cost integer flow problem are considered. Thereby, uncertainty in problem formulation is limited to arc unit costs and expressed by a finite set of explicitly given scenarios. It is shown that both problem variants are NP-hard. To solve the considered variants, several heuristics based on local search or evolutionary computing are proposed. The heuristics are experimentally evaluated on appropriate problem instances.

Keywords

Cite

@article{arxiv.1907.09468,
  title  = {Heuristic solutions to robust variants of the minimum-cost integer flow problem},
  author = {Marko Špoljarec and Robert Manger},
  journal= {arXiv preprint arXiv:1907.09468},
  year   = {2020}
}
R2 v1 2026-06-23T10:27:27.288Z