Solving single machine scheduling problem with maximum lateness using a genetic algorithm

We develop an optimised crossover operator designed by an undirected bipartite graph within a genetic algorithm for solving a single machine family scheduling problem, where jobs are partitioned into families and setup time is required between these families. The objective is to find a schedule whi...

Full description

Bibliographic Details
Main Authors: Nazif, Habibeh, Lee, Lai Soon
Format: Article
Language:English
English
Published: Canadian Center of Science and Education 2010
Subjects:
Online Access:http://psasir.upm.edu.my/id/eprint/16776/
http://psasir.upm.edu.my/id/eprint/16776/1/Solving%20single%20machine%20scheduling%20problem%20with%20maximum%20lateness%20using%20a%20genetic%20algorithm.pdf
_version_ 1848843056240918528
author Nazif, Habibeh
Lee, Lai Soon
author_facet Nazif, Habibeh
Lee, Lai Soon
author_sort Nazif, Habibeh
building UPM Institutional Repository
collection Online Access
description We develop an optimised crossover operator designed by an undirected bipartite graph within a genetic algorithm for solving a single machine family scheduling problem, where jobs are partitioned into families and setup time is required between these families. The objective is to find a schedule which minimises the maximum lateness of the jobs in the presence of the sequence independent family setup times. The results showed that the proposed algorithm is generating better quality solutions compared to other variants of genetic algorithms
first_indexed 2025-11-15T08:08:57Z
format Article
id upm-16776
institution Universiti Putra Malaysia
institution_category Local University
language English
English
last_indexed 2025-11-15T08:08:57Z
publishDate 2010
publisher Canadian Center of Science and Education
recordtype eprints
repository_type Digital Repository
spelling upm-167762015-12-18T03:02:57Z http://psasir.upm.edu.my/id/eprint/16776/ Solving single machine scheduling problem with maximum lateness using a genetic algorithm Nazif, Habibeh Lee, Lai Soon We develop an optimised crossover operator designed by an undirected bipartite graph within a genetic algorithm for solving a single machine family scheduling problem, where jobs are partitioned into families and setup time is required between these families. The objective is to find a schedule which minimises the maximum lateness of the jobs in the presence of the sequence independent family setup times. The results showed that the proposed algorithm is generating better quality solutions compared to other variants of genetic algorithms Canadian Center of Science and Education 2010 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/16776/1/Solving%20single%20machine%20scheduling%20problem%20with%20maximum%20lateness%20using%20a%20genetic%20algorithm.pdf Nazif, Habibeh and Lee, Lai Soon (2010) Solving single machine scheduling problem with maximum lateness using a genetic algorithm. Journal of Mathematics Research, 2 (3). pp. 57-62. ISSN 1916-9795 http://www.ccsenet.org/jmr Scheduling - Mathematical models Genetic algorithms English
spellingShingle Scheduling - Mathematical models
Genetic algorithms
Nazif, Habibeh
Lee, Lai Soon
Solving single machine scheduling problem with maximum lateness using a genetic algorithm
title Solving single machine scheduling problem with maximum lateness using a genetic algorithm
title_full Solving single machine scheduling problem with maximum lateness using a genetic algorithm
title_fullStr Solving single machine scheduling problem with maximum lateness using a genetic algorithm
title_full_unstemmed Solving single machine scheduling problem with maximum lateness using a genetic algorithm
title_short Solving single machine scheduling problem with maximum lateness using a genetic algorithm
title_sort solving single machine scheduling problem with maximum lateness using a genetic algorithm
topic Scheduling - Mathematical models
Genetic algorithms
url http://psasir.upm.edu.my/id/eprint/16776/
http://psasir.upm.edu.my/id/eprint/16776/
http://psasir.upm.edu.my/id/eprint/16776/1/Solving%20single%20machine%20scheduling%20problem%20with%20maximum%20lateness%20using%20a%20genetic%20algorithm.pdf