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Estimation of distribution algorithm for the max-cut problem. (English) Zbl 1382.68235
Kropatsch, Walter G. (ed.) et al., Graph-based representations in pattern recognition. 9th IAPR-TC-15 international workshop, GbRPR 2013, Vienna, Austria, May 15–17, 2013. Proceedings. Berlin: Springer (ISBN 978-3-642-38220-8/pbk). Lecture Notes in Computer Science 7877, 244-253 (2013).
Summary: In this paper, we investigate the max-cut problem and propose a probabilistic heuristic to address its classic and weighted version. Our approach is based on the estimation of distribution algorithm (EDA) that creates a population of individuals capable of evolving at each generation towards the global solution. We have applied the max-cut problem for image segmentation and defined the edges’ weights as a modified function of the L2 norm between the RGB values of nodes. The main goal of this paper is to introduce a heuristic for max-cut and additionally to investigate how it can be applied in the segmentation context.
For the entire collection see [Zbl 1263.68021].

MSC:
68T20 Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.)
68R10 Graph theory (including graph drawing) in computer science
68U10 Computing methodologies for image processing
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