Distributed constraint optimization for continuous mobile sensor coordination

Conference paper (2018)

Authors

J.E. Fransman Team Bart De Schutter - Mechanical, Maritime and Materials Engineering
J. Sijs Team Bart De Schutter - Mechanical, Maritime and Materials Engineering
Erik Theunissen Netherlands Defence Academy
Bart De Schutter Team Bart De Schutter - Mechanical, Maritime and Materials Engineering
Research Group
Team Bart De Schutter (Mechanical, Maritime and Materials Engineering) (TU Delft)
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Published Date

2018

Language

English

Reuse Rights

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Faculty

Mechanical, Maritime and Materials Engineering

Department

Delft Center for Systems and Control

Research Group

Team Bart De Schutter

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 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.

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