Journal article
DESIGN OF CONTROLLABLE LEADER–FOLLOWER NETWORKS VIA MEMETIC ALGORITHMS
Advances in complex systems, Vol.24(2), 2150004
09/25/2021
DOI: 10.1142/S0219525921500041
Abstract
In many engineered and natural networked systems, there has been great interest in leader selection and/or edge assignment during the optimal design of controllable networks. In this paper, we present our pioneering work in leader–follower network design via memetic algorithms, which focuses on minimizing the number of leaders or the amount of control energy while ensuring network controllability. We consider three problems in this paper: (1) selecting the minimum number of leaders in a pre-defined network with guaranteed network controllability; (2) selecting the leaders in a pre-defined network with the minimum control energy; and (3) assigning edges (interactions) between nodes to form a controllable leader–follower network with the minimum control energy. The proposed framework can be applied in designing signed, unsigned, directed, or undirected networks. It should be noted that this work is the first to apply memetic algorithms in the design of controllable networks. We chose memetic algorithms because they have been shown to be more efficient and more effective than the standard genetic algorithms in solving some optimization problems. Our simulation results provide an additional demonstration of their efficiency and effectiveness.
Details
- Title: Subtitle
- DESIGN OF CONTROLLABLE LEADER–FOLLOWER NETWORKS VIA MEMETIC ALGORITHMS
- Creators
- SHAOPING Xiao - University of IowaBAIKE She - Purdue University West LafayetteSIDDHARTHA Mehta - University of FloridaZHEN Kan - University of Science and Technology of China
- Resource Type
- Journal article
- Publication Details
- Advances in complex systems, Vol.24(2), 2150004
- DOI
- 10.1142/S0219525921500041
- ISSN
- 0219-5259
- eISSN
- 1793-6802
- Grant note
- DOI: 10.13039/501100001809, name: National Natural Science Foundation of China, award: 62173314, U2013601
- Language
- English
- Date published
- 09/25/2021
- Academic Unit
- Iowa Technology Institute; Mechanical Engineering
- Record Identifier
- 9984196525802771
Metrics
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