Distributed Constraint Optimization for Continuous Mobile Sensor Coordination

Reference

J. Fransman, J. Sijs, H. Dol, E. Theunissen, and B. De Schutter, "Distributed Constraint Optimization for Continuous Mobile Sensor Coordination," Proceedings of the 2018 European Control Conference, Limassol, Cyprus, pp. 1100-1105, June 2018.

Abstract

DCOP (Distributed Constraint Optimization Problem) is a framework for representing distributed multi-agent problems. However, it only allows discrete values for the decision variables, which limits its application for real-world problems. In this paper, an extension of DCOP is investigated to handle variables with continuous domains. Additionally, an iterative any-time algorithm Compression-DPOP (C-DPOP) is presented that is based on the Distributed Pseudo-tree Optimization Procedure (DPOP). C-DPOP iteratively samples the search space in order to handle problems that are restricted by time and memory limitations. The performance of the algorithm is examined through a mobile sensor coordination problem. The proposed algorithm outperforms DPOP with uniform sampling regarding both resource requirement and performance.

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Bibtex entry

@inproceedings{FraSij:18-014,
author={J. Fransman and J. Sijs and H. Dol and E. Theunissen and B. {D}e Schutter},
title={Distributed Constraint Optimization for Continuous Mobile Sensor Coordination},
booktitle={Proceedings of the 2018 European Control Conference},
address={Limassol, Cyprus},
pages={1100--1105},
month=jun,
year={2018},
doi={10.23919/ECC.2018.8550486}
}

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