Complex network analysis of discrete self-organising migrating algorithm

Abstract

This research analyses the development of a complex network in the swarm based Discrete Self-Organising Migrating Algorithm (DSOMA). The main aim is to evaluate if a complex network is generated in DSOMA, and how the population can be evaluated when the objective is to optimise the flow shop scheduling with blocking problem. The population is evaluated as a complex network over a number of migrations, and different attributes such as adjacency graph, minimal cut, degree centrality, closeness centrality, betweenness centrality, Katz centrality, mean neighbour degree, k-Clique, k-Plan, k-Club, k-Clan and community graph plots are analysed. From the results, it can be concluded that an DSOMA population does behave like a complex network, and therefore can be analysed as such, in order to obtain information about population development. © Springer International Publishing Switzerland 2014