A Cooperative Optimization Algorithm Inspired by Chaos–Order Transition

Abstract EN

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.