Abstract
A multi-stage Hybrid Flow Shop (HFS) scheduling is characterized ‘n’ jobs ‘m’ machines with ‘M’ stages in series with unidirectional flow of work with a variety of jobs being processed sequentially in a single-pass manner. Most real world scheduling problems are NP-hard in nature. The essential complexity of the problem necessitates the use of meta-heuristics for solving hybrid flow shop scheduling problem. The paper addresses multi-stage hybrid flow shop scheduling problems with missing operations to minimize the makespan time with the specific batch size using Genetic Algorithm (GA) and Simulated Annealing algorithm (SA). It is observed that the GA algorithm yields good quality solutions than SA with lesser computational time.
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 callMore From: International Review of Mechanical Engineering (IREME)
Disclaimer: 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.
