[en] Manufacturing scheduling strategies have historically ignored the availability of the machines. The more realistic the schedule, more accurate the calculations and predictions. Availability of machines will play a crucial role in the Industry 4.0 smart factories. In this paper, a mixed integer linear programming model (MILP) and a discrete firefly algorithm (DFA) are proposed for an extended multi-objective FJSP with availability constraints (FJSP-FCR). Several standard instances of FJSP have been used to evaluate the performance of the model and the algorithm. New FJSP-FCR instances are provided. Comparisons among the proposed methods and other state-of-the-art reported algorithms are also presented. Alongside the proposed MILP model, a Genetic Algorithm is implemented for the experiments with the DFA. Extensive investigations are conducted to test the performance of the proposed model and the DFA. The comparisons between DFA and other recently published algorithms shows that it is a feasible approach for the stated problem.
Disciplines :
Computer science
Author, co-author :
Tessaro Lunardi, Willian ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Cherri, Luiz Henrique
Voos, Holger ; University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit
External co-authors :
yes
Language :
English
Title :
A Mathematical Model and a Firefly Algorithm for an Extended Flexible Job Shop Problem with Availability Constraints
Publication date :
June 2018
Event name :
17th International Conference on Artificial Intelligence and Soft Computing (ICAISC 2018)
Event date :
03/06/2018 to 07/06/2018
Audience :
International
Main work title :
17th International Conference on Artificial Intelligence and Soft Computing, Zakopane, Poland, June 3-7, 2018
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