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ThinkMind // COGNITIVE 2017, The Ninth International Conference on Advanced Cognitive Technologies and Applications // View article cognitive_2017_5_40_48007


Sparse Clustered Neural Networks for the Assignment Problem

Authors:
Said Medjkouh
Bowen Xue
Ghouthi Boukli Hacene

Keywords: assignment problem, artificial neural networks, hungarian algorithm.

Abstract:
The linear assignment problem is a fundamental combinatorial problem and a classical linear programming problem. It consists of assigning agents to tasks on a one-to-one basis while minimizing the total assignment cost. The assignment problem appears recurrently in major applications involving optimal decision-making. However, the use of classical solving methods for large size problems is increasingly prohibitive, as it requires high computation and processing cost. In this paper, a biologically inspired algorithm using an artificial neural network (ANN) is proposed. The artificial neural network model involved in this contribution is a sparse clustered neural network (SCN), which is a generalization of the Palm-Wilshaw neural network. The presented algorithm provides a lower complexity compared to the classically used Hungarian algorithm and allows parallel computation at the cost of a fair approximation of the optimal assignment. Illustrative applications through practical examples are given for analysis and evaluation purpose.

Pages: 69 to 75

Copyright: Copyright (c) IARIA, 2017

Publication date: February 19, 2017

Published in: conference

ISSN: 2308-4197

ISBN: 978-1-61208-531-9

Location: Athens, Greece

Dates: from February 19, 2017 to February 23, 2017

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