A Cooperative Optimization Algorithm Inspired by Chaos-Order Transition

Abstract

The growing complexity of optimization problems in distributed systems (DSs) has motivated computer scientists to strive for efficient approaches. This paper presents a novel cooperative algorithm inspired by chaos-order transition in a chaotic ant swarm (CAS). This work analyzes the basic dynamic characteristics of a DS in light of a networked multiagent system at microlevel and models a mapping from state set to self-organization mechanism set under the guide of system theory at macrolevel. A collaborative optimization algorithm (COA) in DS based on the chaos-order transition of CAS is then devised. To verify the validity of the proposed model and algorithm, we solve a locality-based task allocation in a networked multiagent system that uses COA. Simulations show that our algorithm is feasible and effective compared with previous task allocation approaches, thereby illustrating that our design ideas are correct.