Randomized trial finds that Jaya and TLBO algorithms minimize machine idle time and tardiness penalties in manufacturing systems, indicating improved efficiency.
Key Points
This research aims to develop efficient algorithms for scheduling in flexible manufacturing systems, focusing on minimizing idle time and tardiness penalties.
Proposed parameter-less algorithms: Jaya and teaching-learning-based optimization (TLBO)
Utilized multi-objective functions for scheduling in flexible manufacturing cells (FMCs)
Compared effectiveness against public benchmarks
TLBO and Jaya algorithms significantly outperform popular heuristics in minimizing idle time
Demonstrated effective scheduling with reduced tardiness penalties
Achieved optimal production sequences through external and internal job sequence optimization