Detail publikačního výsledku

Two Approaches to Permutation Flow Shop Scheduling Problem

ŠEDA, M.

Originální název

Two Approaches to Permutation Flow Shop Scheduling Problem

Anglický název

Two Approaches to Permutation Flow Shop Scheduling Problem

Druh

Stať ve sborníku v databázi WoS či Scopus

Originální abstrakt

In this paper, two different approaches to permutation flow shop scheduling problem are investigated. The first one is based on a mixed integer programming model and is solved by an optimization package GAMS. As the problem belongs to NP-complete problems, this approach is limited to smaller instances, its reasonable bounds are indicated using benchmarks from OR-Library. For large instances, an approach using genetic algorithm is proposed including its appropriate parameter settings

Anglický abstrakt

In this paper, two different approaches to permutation flow shop scheduling problem are investigated. The first one is based on a mixed integer programming model and is solved by an optimization package GAMS. As the problem belongs to NP-complete problems, this approach is limited to smaller instances, its reasonable bounds are indicated using benchmarks from OR-Library. For large instances, an approach using genetic algorithm is proposed including its appropriate parameter settings

Klíčová slova v angličtině

flow shop, mixed integer programming, heuristic, genetic algorithm

Autoři

ŠEDA, M.

Vydáno

01.06.2002

Nakladatel

Ain Shams University Cairo

Místo

Cairo (Egypt)

ISBN

977-237-172-3

Kniha

Proceedings of the First International Conference on Intelligent Computing and Information Systems ICICIS 2002

Strany od

123

Strany počet

6

BibTex

@inproceedings{BUT10545,
  author="Miloš {Šeda}",
  title="Two Approaches to Permutation Flow Shop Scheduling Problem",
  booktitle="Proceedings of the First International Conference on Intelligent Computing and Information Systems ICICIS 2002",
  year="2002",
  pages="6",
  publisher="Ain Shams University Cairo",
  address="Cairo (Egypt)",
  isbn="977-237-172-3"
}