Flexible Job Shop Optimization with Simulated Annealing

Bachelor thesis (2022)

Authors

M.C. Bak Electrical Engineering, Mathematics and Computer Science

Contributors

M.M. de Weerdt Algorithmics - EEMCS (mentor)
K.C. van den Houten Algorithmics - EEMCS (mentor)
Burcu Kulahcioglu Ozkan Software Engineering - EEMCS (graduation committee member)
Faculty
Electrical Engineering, Mathematics and Computer Science, Electrical Engineering, Mathematics and Computer Science
Copyright: © 2022 Marco Bak
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Published Date

24-06-2022

Language

English

Reuse Rights

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Faculty

Electrical Engineering, Mathematics and Computer Science

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.