Fast computing global structural balance in signed networks based on memetic algorithm

Yixiang Sun, Haifeng Du, Maoguo Gong, Lijia Ma and Shanfeng Wang

Physica A: Statistical Mechanics and its Applications, 2014, vol. 415, issue C, 261-272

Abstract: Structural balance is a large area of study in signed networks, and it is intrinsically a global property of the whole network. Computing global structural balance in signed networks, which has attracted some attention in recent years, is to measure how unbalanced a signed network is and it is a nondeterministic polynomial-time hard problem. Many approaches are developed to compute global balance. However, the results obtained by them are partial and unsatisfactory. In this study, the computation of global structural balance is solved as an optimization problem by using the Memetic Algorithm. The optimization algorithm, named Meme-SB, is proposed to optimize an evaluation function, energy function, which is used to compute a distance to exact balance. Our proposed algorithm combines Genetic Algorithm and a greedy strategy as the local search procedure. Experiments on social and biological networks show the excellent effectiveness and efficiency of the proposed method.

Keywords: Signed network; Structural balance; Global property; Memetic algorithm; Genetic algorithm; Local search (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (7)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:415:y:2014:i:c:p:261-272

DOI: 10.1016/j.physa.2014.07.071

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