Searched for: subject%3A%22Lagrangian%255C%2BRelaxation%22
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document
Schöpe, M.I. (author)
Recent advances in Multi-Function Radar (MFR) systems led to an increase in their degrees of freedom. As a result, modern MFR systems are capable of adjusting many parameters during runtime. An automatic adaptation of the radar system to changing situations, like weather conditions, interference, or target maneuvers, is often mentioned in the...
doctoral thesis 2021
document
Schöpe, M.I. (author), Driessen, J.N. (author), Yarovoy, Alexander (author)
The radar resource management problem in a multitarget tracking scenario is considered. The problem is solved using a dynamic budget balancing algorithm. It models the different sensor tasks as partially observable Markov decision processes and solves them by applying a combination of Lagrangian relaxation and policy rollout. The algorithm has a...
journal article 2021
document
Schöpe, M.I. (author), Driessen, J.N. (author), Yarovoy, Alexander (author)
The radar resource management problem in a multitarget tracking scenario for multi-function radar is considered. To solve it, an optimal balancing of the sensor budget by applying Lagrangian relaxation and the subgradient method is proposed. In a time-invariant scenario it is shown that the proposed method will lead to balanced budgets based on...
conference paper 2020
document
Liang, X. (author), Correia, Gonçalo (author), An, Kun (author), van Arem, B. (author)
In this paper, we study the dial-a-ride problem of ride-sharing automated taxis (ATs) in an urban road network, considering the traffic congestion caused by the ATs. This shared automated mobility system is expected to provide a seamless door-to-door service for urban travellers, much like what the existing transportation network companies ...
journal article 2020
document
Schöpe, M.I. (author), Driessen, J.N. (author), Yarovoy, Alexander (author)
The sensor resource management problem in a multi-object tracking scenario is considered. In order to solve it, a dynamic budget balancing algorithm is proposed which models the different sensor tasks as partially observable Markov decision processes. Those are being solved by applying a combination of Lagrangian relaxation and policy rollout....
conference paper 2020
Searched for: subject%3A%22Lagrangian%255C%2BRelaxation%22
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