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113. Multi-objective Optimization of Retrial Machine Repair Problem with Warm Standbys and Working Vacation
Invited abstract in session MC-52: Multi-objective Combinatorial Optimization, stream Combinatorial Optimization.
Monday, 12:30-14:00Room: 8003 (building: 202)
Authors (first author is the speaker)
| 1. | Kuo-Hsiung Wang
|
| Business Administration, Asia University |
Abstract
Abstract:
This study investigates the retrial machine repair problem with warm standbys and working vacation, in which the server works with different repair rates rather than completely halting the repair during a vacation period. It is assumed that the server begins working vacation when the system is empty. When a failed machine finds that the server is idle upon arrival, it is immediately repaired by the server. If the failed machine finds that the server is busy upon arrival, it leaves the repair facility to join the retrial orbit and attempts repair again. The failure, repair, vacation, and retrial times are assumed to be exponentially distributed. A matrix analytic method was used to compute steady-state probabilities and several system performance measures. A multi-objective model for the cost and expected waiting time was derived. The epsilon-constraint method and non-dominated sorting genetic algorithm were used to identify and compare the Pareto optimal set and make comparisons. The Pareto front set was obtained and illustrated to improve the quality of decision making for system engineers.
Keywords
- Queuing Systems
- Optimization Modeling
- Stochastic Models
Status: accepted
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