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http://hdl.handle.net/10225/803
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| Title: | ADAPTIVE, MULTI-OBJECTIVE JOB SHOP SCHEDULING USING GENETIC ALGORITHMS |
| Authors: | Metta, Haritha |
| Keywords: | Genetic Algorithms
Job shop scheduling
Multi-objective optimization
Adaptive scheduling
Asexual reproduction |
| Date Created: | 2008 |
| Publisher: | University of Kentucky |
| Abstract: | This research proposes a method to solve the adaptive, multi-objective job shop scheduling problem. Adaptive scheduling is necessary to deal with internal and external disruptions faced in real life manufacturing environments. Minimizing the mean tardiness for jobs to effectively meet customer due date requirements and minimizing mean flow time to reduce the lead time jobs spend in the system are optimized simultaneously. An asexual reproduction genetic algorithm with multiple mutation strategies is developed to solve the multi-objective optimization problem. The model is tested for single day and multi-day adaptive scheduling. Results are compared with those available in the literature for standard problems and using priority dispatching rules. The findings indicate that the genetic algorithm model can find good solutions within short computational time. |
| URI: | http://hdl.handle.net/10225/803 |
| Appears in Collections: | Electronic Theses and Dissertations
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Size | Format |
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| Thesis.pdf | | 2018Kb | Adobe PDF | View/Open |
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