Abstract
The paper studies the scheduling problem in a Flexible Manufacturing System (FMS) operating under uncertain environment. Depending upon the intensity, nature and information, the uncertainties are classified into: (1) completely unknown, (2) suspicious, and (3) known uncertainties. An objective function has been formulated that incorporate all sort of uncertainty
in order to evaluate the performance measures of an FMS. Makespan has been considered as objective measures to evaluate the performance of FMS. The objective measure has been determined on ten randomly generated dataset. A total of 12 cases have been considered for each flexibility level under each dataset. Flexibility level has been used as a variable to analyse the performance of FMS under these cases. A nature inspired random search technique, viz. Symbiotic Evolutionary Algorithm (SEA), has been used to solve thescheduling problem under different cases considered. To delineate the supremacy of SEA on the FMS planning and scheduling problem, results are compared with the well-established priority-based dispatching rules.
in order to evaluate the performance measures of an FMS. Makespan has been considered as objective measures to evaluate the performance of FMS. The objective measure has been determined on ten randomly generated dataset. A total of 12 cases have been considered for each flexibility level under each dataset. Flexibility level has been used as a variable to analyse the performance of FMS under these cases. A nature inspired random search technique, viz. Symbiotic Evolutionary Algorithm (SEA), has been used to solve thescheduling problem under different cases considered. To delineate the supremacy of SEA on the FMS planning and scheduling problem, results are compared with the well-established priority-based dispatching rules.
Original language | English |
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Pages (from-to) | 45-70 |
Number of pages | 26 |
Journal | International Journal of Services Operations and Informatics |
Volume | 6 |
Issue number | 1/2 |
DOIs | |
Publication status | Published - 2011 |
Keywords
- flexible manufacturing system
- uncertainties
- machine flexibility
- random search algorithm
- scheduling