Abstract
Scheduling problems can be fuzzified by introducing the concept of fuzzy due date; the membership function of a fuzzy due date assigned to each job represents the grade of satisfaction of the decision maker for the completion time of that job. The aim of this paper is to show the relations between the fuzzy scheduling problems and conventional scheduling problems with earliness and tardiness penalties. It is shown that a genetic algorithm can find the optimal solutions of the conventional scheduling problems by solving the fuzzy scheduling problems.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
