Reference
A. N. Tarău, 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.
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BibTeX
@article{TarDeS:10-020,
author = {Tar{\u{a}}u, Alina N. and De Schutter, Bart and Hellendoorn,
Johannes},
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}
}