Study on the Time Development of Complex Network for Metaheuristic

Abstract

This work deals with the hybridization of the complex networks framework and evolutionary algorithms. The population is visualized as an evolving complex network, which exhibits non-trivial features. This paper investigates briefly the time development of complex network within the run of selected metaheuristic algorithm, which is Differential Evolution (DE). This paper also briefly discuss possible utilization of the complex network attributes such as adjacency graph, centralities, clustering coefficient and others. Experiments were performed for one selected DE strategy and one simple test function.

Dynamic of Firework Algorithm Analyzed with Complex Network

“…The network is created as a history of contributions. Despite the fact that the inner dynamic of evolutionary algorithms has been transferred to the complex network multiple times [9][10][11][12], the FWA and its unique communication scheme required a development of a new technique, which is proposed in this section. In each iteration, there are NP fireworks.…”

“…This complex networks can be more analyzed using different techniques [7,8]. Typically, this analysis is made on Swarm Intelligence (SI) algorithms [9][10][11][12] which have some social behavior or communication across particles. This social behavior can be transferred into the complex network.…”

Uncovering Communication Density In PSO Using Complex Network

“…premature convergence). Recently the interconnection between metaheuristics and complex networks (CNs) has been (Zelinka 2011a, 2011b, 2013, Senkerik et al, 2016 with interesting results (Davendra, 2014a(Davendra, , 2014b. We take inspiration in above mentioned examples of interconnection of metaheuristics and CNs and use the network-style visualization to uncover the density of communication in the PSO.…”