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IEAAIE
2005
Springer

A Fuzzy Genetic Algorithm for Real-World Job Shop Scheduling

8 years 8 months ago
A Fuzzy Genetic Algorithm for Real-World Job Shop Scheduling
In this paper, a multi-objective genetic algorithm is proposed to deal with a real-world fuzzy job shop scheduling problem. Fuzzy sets are used to model uncertain due dates and processing times of jobs. The objectives considered are average tardiness and the number of tardy jobs. Fuzzy sets are used to represent satisfaction grades for the objectives taking into consideration the preferences of the decision maker. A genetic algorithm is developed to search for the solution with maximum satisfaction grades for the objectives. The developed algorithm is tested on real-world data from a printing company. The experiments include different aggregation operators for combining the objectives.
Carole Fayad, Sanja Petrovic
Added 27 Jun 2010
Updated 27 Jun 2010
Type Conference
Year 2005
Where IEAAIE
Authors Carole Fayad, Sanja Petrovic
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