Sales potential optimization on directed social networks: a quasi-parallel genetic algorithm approach

Authors:
Crown Guan Wang;Kwok Yip Szeto
Affiliations:
Department of Physics, The Hong Kong University of Science and Technology, HKSAR, Hong Kong,China;Department of Physics, The Hong Kong University of Science and Technology, HKSAR, Hong Kong,China
Venue:
EvoApplications'12 Proceedings of the 2012t European conference on Applications of Evolutionary Computation
Year:
2012

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Abstract

New node centrality measurement for directed networks called the Sales Potential is introduced with the property that nodes with high Sales Potential have small in-degree and high second-shell in-degree. Such nodes are of great importance in online marketing strategies for sales agents and IT security in social networks. We propose an optimization problem that aims at finding a finite set of nodes, so that their collective Sales Potential is maximized. This problem can be efficiently solved with a Quasi-parallel Genetic Algorithm defined on a given topology of sub-populations. We find that the algorithm with a small number of sub-populations gives results with higher quality than one with a large number of sub-populations, though at the price of slower convergence.