Detail publikace

Application of Genetic Algorithms to Scheduling and Lot Sizing in a Flow Shop

DVOŘÁK, J., MAJER, P.

Originální název

Application of Genetic Algorithms to Scheduling and Lot Sizing in a Flow Shop

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

In this paper, we investigate a problem of integrated lot sizing and scheduling in a permutation flow shop under the assumption of constant continuous demands over an infinite planning horizon. The objective is to find a sequence of production and lot sizes that minimise the sum of average set-up costs and average inventory holding costs. We study three approaches based on genetic algorithms. The first approach deals with only one population of individuals consisting of the part coding lot sizes and the part of product sequence. Genetic operators are randomly applied either to the parts of lot sizes or to the parts of product sequence. In the second approach there are two populations. In the first population the lot sizes parts are improved and in the second one the product sequences are improved. Selected individuals migrate between these populations. The third approach alternates solving two problems: the lot-sizing problem with a fixed sequence of products and the scheduling problem with fixed lot sizes. Computational results are presented and compared.

Klíčová slova v angličtině

flow shop, lot sizing, scheduling, genetic algorithms

Autoři

DVOŘÁK, J., MAJER, P.

Rok RIV

2000

Vydáno

1. 6. 2000

Nakladatel

PC-DIR Brno

Místo

Brno, Czech Republic

ISBN

80-214-1609-2

Kniha

6th International Conference on Soft Computing MENDEL 2000

Strany od

45

Strany do

51

Strany počet

7

BibTex

@inproceedings{BUT1833,
  author="Jiří {Dvořák} and Petr {Majer}",
  title="Application of Genetic Algorithms to Scheduling and Lot Sizing in a Flow Shop",
  booktitle="6th International Conference on Soft Computing MENDEL 2000",
  year="2000",
  pages="7",
  publisher="PC-DIR Brno",
  address="Brno, Czech Republic",
  isbn="80-214-1609-2"
}