Abstract
It was mentioned in Chapter 4 that in sequencing jobs in a flowshop we are likely to confront several different (and often conflicting) management objectives. Consequently, a schedule may have to be evaluated by different types of performance measures. Some of these measures may give importance to completion time (e.g. makespan), some to due date (e.g. mean tardiness, maximum tardiness), and some others to the speed with which the jobs flow (e.g. mean flow time). The simultaneous consideration of these objectives is a multiobjective optimization problem. But, even for a single objective, flowshop sequencing is NP-hard. Therefore, solving even a single objective flowshop problem involving only 15-20 machines and 30-40 jobs by classical optimization methods would be quite difficult.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 1999 Springer Science+Business Media New York
About this chapter
Cite this chapter
Bagchi, T.P. (1999). Multiobjective Flowshop Scheduling. In: Multiobjective Scheduling by Genetic Algorithms. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-5237-6_9
Download citation
DOI: https://doi.org/10.1007/978-1-4615-5237-6_9
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4613-7387-2
Online ISBN: 978-1-4615-5237-6
eBook Packages: Springer Book Archive