Multi-objective flow shop scheduling problem with stochastic parameters: fuzzy goal programming approach Online publication date: Fri, 31-Oct-2014
by Donya Rahmani; Reza Ramezanian; Mohammad Saidi-Mehrabad
International Journal of Operational Research (IJOR), Vol. 21, No. 3, 2014
Abstract: Flow shop scheduling problem with stochastic parameters is dealt with in this paper. A multi-objective mixed integer linear programming model is proposed in this concern which can generate non-permutation schedules. To provide a more realistic model, process time and release time are considered stochastic variables with normal distribution. The objective functions are minimising three performance measures including maximum completion time (Makespan), total flow time and total tardiness. Chance constrained programming (CCP) approach and fuzzy goal programming (FGP) are applied to deal with the stochastic parameters and multi-objective function. Due to the complexity of the problem, we have implemented an adapted genetic algorithm to solve large-sized problem. According to the computational experiments, the GA can reach good-quality solutions in reasonable computational time, and can be used to solve large scale problems effectively.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Operational Research (IJOR):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook