Distributed constraint optimization for continuous mobile sensor coordination

Distributed constraint optimization for continuous mobile sensor coordination

Fransman, J.
Sijs, J.
Dol, H.S.
Theunissen, E.
de Schutter, B.D.

2018

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 Opti- mization 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. © 2018 European Control Association (EUCA).

Constrained optimization
Multi agent systems
Trees (mathematics)
Any-time algorithms
Continuous domain
Decision variables
Distributed constraint optimizations
Multi-agent problems
Real-world problem
Resource requirements
Uniform sampling
Iterative methods

http://resolver.tudelft.nl/uuid:9873b4bd-f015-412d-b3fc-2b2e6fecee05

861665

Institute of Electrical and Electronics Engineers Inc.

9783952426982

2018 European Control Conference, ECC 2018, 16th European Control Conference, ECC 2018, 12 June 2018 through 15 June 2018, 1100-1105

8550486

Sponsor: European Control Association (EUCA)

conference paper