Topology optimization for optimal target control of complex networks

¹ Adaptive Networks and Control Lab, Department of Electronic Engineering, School of Information Science and Engineering, Fudan University - Shanghai 200433, China
² Research Institute of Intelligent Complex Systems, Fudan University - Shanghai 200433, China

Received: 20 March 2025
Accepted: 28 July 2025

Abstract

The study of control energy needed for controlling target nodes is essential for efficient operation of network systems. Previous studies on control energy in networks have primarily focused on fully controllable network systems, with the main emphasis on optimizing the selection of driver nodes. In order to reduce the required energy for controlling target nodes, we propose the greedy algorithm based on target path (GATP) to optimize network topology by adding only a few edges. By shortening the distance between target nodes and driver nodes, the proposed GATP significantly reduces the energy required to control the target nodes in complex networks. The simulation results on Erdős-Rényi, scale-free, and real-world networks demonstrate that target paths play a crucial role in optimizing control energy for controlling target nodes, and that GATP outperforms random allocation, genetic algorithms, and simulated annealing.