Article ID: | iaor20052524 |
Country: | Netherlands |
Volume: | 48 |
Issue: | 3 |
Start Page Number: | 491 |
End Page Number: | 506 |
Publication Date: | May 2005 |
Journal: | Computers & Industrial Engineering |
Authors: | Gupta Jatinder N.D., Moscato Pablo, Frana Paulo M., Mendes Alexandre S., Veltink Klaas J. |
Keywords: | heuristics |
This paper considers the problem of scheduling part families and jobs within each part family in a flowshop manufacturing cell with sequence dependent family setups times where it is desired to minimize the makespan while processing parts (jobs) in each family together. Two evolutionary algorithms – a Genetic Algorithm and a Memetic Algorithm with local search – are proposed and empirically evaluated as to their effectiveness in finding optimal permutation schedules. The proposed algorithms use a compact representation for the solution and a hierarchically structured population where the number of possible neighborhoods is limited by dividing the population into clusters. In comparison to a Multi-Start procedure, solutions obtained by the proposed evolutionary algorithms were very close to the lower bounds for all problem instances. Moreover, the comparison against the previous best algorithm, a heuristic named CMD, indicated a considerable performance improvement.