Enhancing Robustness and Transmission Performance of Heterogeneous Complex Networks via Multiobjective Optimization

Transmission networks are ubiquitous in modern society and play critical roles in facilitating the delivery and movement of information, power, and people between various locations. Robustness and transmission capacity are two pivotal and universal properties of practical networks, and much research effort has been devoted to investigating these two properties in the past decade. In this article, we consider a heterogeneous transmission network consisting of hosts and routers and aim to optimize both transmission capacity and robustness of this network simultaneously. To solve this problem, we propose a multiobjective evolutionary algorithm (MOEA) for optimizing transmission capacity and robustness. Moreover, in order to achieve optimized transmission performance and robustness at reasonable and balanced computational cost, the proposed MOEA adopts a two-phase design, i.e., a sampling phase and an optimization phase. Simulation results on scale-free and realistic transmission networks demonstrate the effectiveness of the proposed algorithm. Moreover, comprehensive analysis of the solutions from different parts of the obtained Pareto fronts shows distinct characteristics and provides various choices for optimizing transmission functionality and robustness of networks.