Compositional optimization of large-scale discrete event systems
This thesis proposes a new method of solving these optimization problems using a compositional optimization approach. This integrates optimization with techniques from compositional supervisory control, dividing the optimization of subsystems into separate sub-problems.
The key to this approach is the identification of local behavior in subsystems, behavior that is independent of all other subsystems. It is proven in this thesis that this local behavior can be optimized individually without affecting the global optimal solution. This is used by the approach, to reduce the state space in each subsystem, and then to utilize these reduced models compositionally when the global optimal solution is computed.
Results in this thesis show that compositional optimization efficiently can generate global optimal solutions to large-scale optimization problems, too big to solve based on traditional monolithic models. It is also shown that these techniques can be applied to several industrial applications, e.g. in logistics, manufacturing etc.
Discrete Event Systems
Chalmers, Elektroteknik, System- och reglerteknik, Automation
Time-optimal control of large-scale systems of systems using compositional optimization
Discrete Event Dynamic Systems: Theory and Applications,; Vol. 29(2019)p. 411-443
Artikel i vetenskaplig tidskrift
Compositional Optimization of Discrete Event Systems
IEEE International Conference on Automation Science and Engineering,; Vol. 2018-August(2018)p. 849-856
Paper i proceeding
Comparing MILP, CP, and A* for Multiple Stacker Crane Scheduling
Proc. 13th International Workshop on Discrete Event Systems (WODES’16), Xi’an, China, May,; (2016)p. 63-70
Paper i proceeding
Robotteknik och automation
Chalmers tekniska högskola