**Reference:**

A.N. Tarau,
B. De Schutter, and
J. Hellendoorn,
"Predictive route control for automated baggage handling systems using
mixed-integer linear programming," *Transportation Research Part
C*, vol. 19, no. 3, pp. 424-439, June 2011.

**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 network of tracks. In this
paper we consider the problem of controlling the route of each DCV in
the system. In general this results in a nonlinear, nonconvex,
mixed-integer optimization problem, usually very expensive in terms of
computational effort. Therefore, 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
problems solvers are available that 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. We use model predictive control (MPC) for
solving the route choice problem. To assess the performance of the
proposed (nonlinear and MILP) formulations 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 (277 KB)

@article{TarDeS:10-020,

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

title={Predictive route control for automated baggage handling systems using mixed-integer linear programming},

journal={Transportation Research Part C},

volume={19},

number={3},

pages={424--439},

month=jun,

year={2011},

doi={10.1016/j.trc.2010.06.004}

}

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