Abstract
In this paper, we consider the problem of scheduling N robots interacting with a moving target. Both, the sequence of the robots and their trajectories are unknown and subject to optimization. Such type of problems appear in highly automated production plants and in the simulation of virtual factories. The purpose of the paper is to provide a mathematical model and to suggest a numerical solution approach. Our approach is based on the formulation of the problem as a bilevel optimization problem, where the lower level problem is an optimal control problem, while the upper level problem is a finite dimensional mixed-integer optimization problem. We approach the problem by exploitation of necessary optimality conditions for the lower level problem and by application of a Branch & Bound method for the resulting single level optimization problem. Two settings are taken into account. Firstly, no state constraints are assumed on the lower level problem, thus the local minimum principle applies directly. Secondly, the problem setting is augmented by pure state constraints, which are being handled by virtual controls in order to regularize the problem.
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Palagachev, K.D., Gerdts, M. (2017). Numerical Approaches Towards Bilevel Optimal Control Problems with Scheduling Tasks. In: Ghezzi, L., Hömberg, D., Landry, C. (eds) Math for the Digital Factory. Mathematics in Industry(), vol 27. Springer, Cham. https://doi.org/10.1007/978-3-319-63957-4_10
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DOI: https://doi.org/10.1007/978-3-319-63957-4_10
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