Flexible Job Shop Optimization with Simulated Annealing
M.C. Bak (TU Delft - Electrical Engineering, Mathematics and Computer Science)
M.M. de Weerdt – Mentor (TU Delft - Electrical Engineering, Mathematics and Computer Science)
K.C. van den Houten – Mentor (TU Delft - Electrical Engineering, Mathematics and Computer Science)
B. Özkan – Graduation committee member (TU Delft - Electrical Engineering, Mathematics and Computer Science)
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Abstract
In this paper, a Simulated Annealing (SA) implementation for a Flexible Job Shop Problem (FJSP), with change-over time, is presented.
This implementation is compared to a Mixed Integer Linear Programming (MILP) optimization, to compare performances.
The SA algorithm starts with creating the first schedule with Global Selection.
The neighbourhood is created with an application of k-insertion.
Annealing is implemented with exponential cooling.
The SA implementation does not consistently outperform the provided MILP implementation. However, the run-time of the simulated annealing is shorter than the MILP.
The algorithm is then also used to discover bottlenecks in the production line presented with the FJSP instances.