**Reference:**

A.N. Tarau,
B. De Schutter, and
J. Hellendoorn,
"Predictive route choice control of destination coded vehicles with
mixed integer linear programming optimization," *Proceedings of the
12th IFAC Symposium on Transportation Systems*, Redondo Beach,
California, pp. 64-69, Sept. 2009.

**Abstract:**

State-of-the-art baggage handling systems transport luggage in an
automated way using destination coded vehicles (DCVs). These vehicles
transport the bags at high speeds on a "mini" railway network. In this
paper we consider the problem of controlling the route of each DCV in
the system. This is a nonlinear, nonconvex, mixed integer optimization
problem. Nonlinear model predictive control (MPC) for mixed integer
problems is usually very expensive in terms of computational effort.
Therefore, in this paper we present an alternative approach for
reducing the complexity of the computations by simplifying and
approximating the nonlinear optimization problem by a mixed integer
linear programming (MILP) problem. The advantage is that for MILP
optimization problems solvers are available to allow us to efficiently
compute the global optimal solution. The solution of the MILP problem
can then be used as a good initial starting point for the original
nonlinear optimization problem. To assess the performance of the
proposed formulation of the MPC optimization problem, we consider a
benchmark case study, the results being compared for several
scenarios.

Online version of the paper

Corresponding technical report: pdf file (138 KB)

@inproceedings{TarDeS:09-030,

author={A.N. Tar{\u{a}}u and B. {D}e Schutter and J. Hellendoorn},

title={Predictive route choice control of destination coded vehicles with mixed integer linear programming optimization},

booktitle={Proceedings of the 12th IFAC Symposium on Transportation Systems},

address={Redondo Beach, California},

pages={64--69},

month=sep,

year={2009},

doi={10.3182/20090902-3-US-2007.0035}

}

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