Solving hybrid flow shop scheduling problems using bat algorithm

M.K. Marichelvam, T. Prabaharan, Xin-She Yang and M. Geetha

International Journal of Logistics Economics and Globalisation, 2013, vol. 5, issue 1, 15-29

Abstract: This paper investigates the multistage hybrid flow shop (HFS) scheduling problems using the new bat algorithm. A HFS is the generalisation of flowshop with multiple machines. HFS is one of the important scheduling problems that represent many industries like iron and steel, chemical, textile and ceramic industries. The HFS scheduling problems have been proved to be NP-hard. A recently developed bat meta-heuristic algorithm is proposed to solve the HFS problems. The proposed algorithm is validated with a well-chosen set of benchmark problems in the literature. Computational results indicate that the proposed bat algorithm is more efficient than the genetic algorithm and particle swarm optimisation.

Keywords: hybrid flow shop scheduling; HFS scheduling; NP-hard; bat algorithm; makespan; metaheuristics; genetic algorithms; particle swarm optimisation; PSO. (search for similar items in EconPapers)
Date: 2013
References: Add references at CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://www.inderscience.com/link.php?id=54428 (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:ids:injleg:v:5:y:2013:i:1:p:15-29

Access Statistics for this article

More articles in International Journal of Logistics Economics and Globalisation from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().