A shuffled frog-leaping algorithm with memeplex quality for bi-objective distributed scheduling in hybrid flow shop

Hybrid flow shop scheduling problem has been extensively considered in single factory; however, distributed hybrid flow shop scheduling problem (DHFSP) is seldom investigated in multiple factories and should be studied fully with the applications of distributed manufacturing. In this study, DHFSP wi...

Full description

Saved in:
Bibliographic Details
Published in:International journal of production research 2021-09, Vol.59 (18), p.5404-5421
Main Authors: Cai, Jingcao, Lei, Deming, Li, Ming
Format: Article
Language:English
Subjects:
Algorithms
distributed scheduling
Hybrid flow shop
Industrial plants
Job shop scheduling
memeplex quality
multi-objective optimisation
Search process
shuffled frog-leaping algorithm
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Hybrid flow shop scheduling problem has been extensively considered in single factory; however, distributed hybrid flow shop scheduling problem (DHFSP) is seldom investigated in multiple factories and should be studied fully with the applications of distributed manufacturing. In this study, DHFSP with sequence-dependent setup times is considered, in which factory assignment and machine assignment of first stage are integrated together. A new shuffled frog-leaping algorithm with memeplex quality (MQSFLA) is proposed to minimise total tardiness and makespan simultaneously. Solution quality of memeplex is measured and new search process is implemented according to solution quality. Evolution quality is evaluated for each memeplex and adopted for dynamically selecting memeplexes in a novel memeplex shuffling. A number of experiments are conducted to test the new strategies and performances of MQSFLA. The computational results demonstrate the effectiveness of the new strategies and the promising advantages of MQSFLA.
ISSN:0020-7543
1366-588X
DOI:10.1080/00207543.2020.1780333