Abstract
We propose a rule-based dynamic definition of weight values for multi-objective fuzzy scheduling problems with the OWA operator. When we employ the scheme of the OWA operator for multi-objective fuzzy scheduling problems, we should assign the weight vector w in advance. Therefore, we propose a rule-based weight definition method in order to reduce the effort to define the weight values in the OWA operator. In our multi-objective fuzzy scheduling problems, we take account of the importance of each job. That is, we use a different unit reward for the satisfaction grade of each job. We employ a genetic algorithm to maximize the fitness function, which is the function with the OWA operator. Finally, we show that the introduction of the rule-based weight definition method is effective for finding solutions.
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.
