The Cooperative Optimization Metaheuristic: Inspiration from Nature and Applications

The cooperative optimization is a newly discovered metaheuristic for solving difficult combinatorial optimization problems. It is inspired by the cooperation principle in social systems where individuals in a system often work together in a cooperative way to solve hard problems of a complexity beyond the capability of any individual in the system. Unlike any existing metaheuristics, it has a number of global optimality conditions so that the cooperative optimization algorithms know where to find global optima and when to stop searching. Furthermore, a cooperative optimization algorithm has a unique equilibrium and converges to it with an exponential rate regardless of initial conditions and perturbations. In solving real-world optimization problems, the cooperative optimization algorithms have often significantly outperformed state-of-the-art algorithms.

Authors and Affiliations

1. Coding Research, Foster City, CA 94404, USA

   Xiaofei Huang

Editors and Affiliations

1. Institute of Intelligent Machines , Chinese Academy of Sciences , Anhui, Hefei, China

   De-Shuang Huang

2. Queen’s University , Belfast, UK

   Kang Li  & George William Irwin  & 

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