Genetic algorithm for the permutation flow-shopscheduling problem with linear models of operations

Adam Janiak and Marie-Claude Portmann

Annals of Operations Research, 1998, vol. 83, issue 0, 95-114

Abstract: The paper deals with a permutation flow-shop problem where processing times of jobs on some machines are linear, decreasing functions with respect to the amount of continuously-divisible, non-renewable, locally and totally constrained resources, e.g. energy, catalyzer, raw materials, etc. The purpose is to find a processing order of jobs that is the same on each machine and a resource allocation that minimizes the length of the time required to complete all jobs, i.e. makespan. Since the problem is strongly NP-hard, some heuristic algorithms of a genetic type were applied to solve it. These algorithms strongly employ some substantial problem properties, which were proved. The results of some computational experiments are also included. Copyright Kluwer Academic Publishers 1998

Date: 1998
References: Add references at CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://hdl.handle.net/10.1023/A:1018924517216 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:annopr:v:83:y:1998:i:0:p:95-114:10.1023/a:1018924517216

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10479

DOI: 10.1023/A:1018924517216

Access Statistics for this article

Annals of Operations Research is currently edited by Endre Boros

More articles in Annals of Operations Research from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().