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Sensitivity Analysis of Predictive Scheduling Algorithms
- Source :
- Advanced Materials Research. 1036:921-926
- Publication Year :
- 2014
- Publisher :
- Trans Tech Publications, Ltd., 2014.
-
Abstract
- In the paper a survey of predictive and reactive scheduling methods is done in order to evaluate how ability of prediction of reliability characteristics influence over robustness criteria. Survey analysis is done for two job shop scheduling problems: 5x8 and 5x10. The paper answers the question: what method generates robust schedules in case of a failure of a bottleneck occurrence before or after maintenance actions? The Hybrid - Multi Objective Immune Algorithm (H-MOIA) is aided with heuristics: Minimal Impact of Disturbed Operation on the Schedule (MIDOS) for predictive scheduling and Minimal Impact of Rescheduled Operation on the Schedule (MIROS) for reactive scheduling. Sensitivity analysis is done for predictive scheduling methods 1) H-MOIA +MIDOS, 2) algorithm based on priority rules: the Least Flexible Job First (LFJ) and the Longest Processing Time (LPT) and 3) the Average Slack Method. Reactive schedules are generated for various scenarios of the bottleneck occurrence in order to evaluate the efficiency of predictive scheduling methods. Reactive schedules are generated using 1) H-MOIA+MIROS, 2) Right Shifting, 3) rescheduling disturbed operations to parallel machines first available. Efficiency of predictive schedules is evaluated using criteria: makespan, total tardiness, flow time, idle time. Efficiency of reactive schedules is evaluated using: solution robustness criterion and quality robustness criterion.
- Subjects :
- Earliest deadline first scheduling
Rate-monotonic scheduling
Schedule
Mathematical optimization
Job shop scheduling
Job shop
Least slack time scheduling
Computer science
Tardiness
General Engineering
Flow shop scheduling
Dynamic priority scheduling
Bottleneck
Fair-share scheduling
Scheduling (computing)
Heuristics
Subjects
Details
- ISSN :
- 16628985
- Volume :
- 1036
- Database :
- OpenAIRE
- Journal :
- Advanced Materials Research
- Accession number :
- edsair.doi...........5cbb78b5a1c01917e1450037acdfe1d3