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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

A Cooperative Optimization Algorithm Inspired by Chaos–Order Transition