Solving Single Machine Scheduling Problem with Maximum Lateness Using a Genetic Algorithm

Habibeh NAZIF, Lai Soon LEE


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.

Full Text:



Journal of Mathematics Research   ISSN 1916-9795 (Print)   ISSN 1916-9809 (Online)

Copyright © Canadian Center of Science and Education

To make sure that you can receive messages from us, please add the '' domain to your e-mail 'safe list'. If you do not receive e-mail in your 'inbox', check your 'bulk mail' or 'junk mail' folders.