A quantum-inspired ant colony optimization for robot coalition formation

Authors:
Zhang Yu;Liu Shuhua;Fu Shuai;Wu Di
Affiliations:
School of Computer Science, Northeast Normal University, Changchun;School of Computer Science, Northeast Normal University, Changchun;School of Computer Science, Northeast Normal University, Changchun;School of Computer Science, Northeast Normal University, Changchun
Venue:
CCDC'09 Proceedings of the 21st annual international conference on Chinese Control and Decision Conference
Year:
2009

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Abstract

A Quantum-Inspired Ant Colony Optimization (QACO), based on the concept and principles of quantum computing is proposed in this paper to improve the ability to search and optimization of Ant Colony Optimization (ACO). Each ant is a quantum individual and instead of Q-bit code, we use the probability of choosing robots, and QACO is successfully applied to solve robot coalition formation. The simulated results show that QACO has the better diversity of population and ability to search and optimization, and performs well, even with a small population, without premature convergence as compared to ACO.