Intruder alert! Optimization models for solving the mobile robot graph-clear problem View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2018-07

AUTHORS

Michael Morin, Margarita P. Castro, Kyle E. C. Booth, Tony T. Tran, Chang Liu, J. Christopher Beck

ABSTRACT

We develop optimization approaches to the graph-clear problem, a pursuit-evasion problem where mobile robots must clear a facility of intruders. The objective is to minimize the number of robots required. We contribute new formal results on progressive and contiguous assumptions and their impact on algorithm completeness. We present mixed-integer linear programming and constraint programming models, as well as new heuristic variants for the problem, comparing them to previously proposed heuristics. Our empirical work indicates that our heuristic variants improve on those from the literature, that constraint programming finds better solutions than the heuristics in run-times reasonable for the application, and that mixed-integer linear programming is superior for proving optimality. Given their performance and the appeal of the model-and-solve framework, we conclude that the proposed optimization methods are currently the most suitable for the graph-clear problem. More... »

PAGES

335-354

References to SciGraph publications

Journal

TITLE

Constraints

ISSUE

3

VOLUME

23

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s10601-018-9288-3

DOI

http://dx.doi.org/10.1007/s10601-018-9288-3

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1104134112


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