  Often times, individuals working together as a team can solve hard problems
beyond the capability of any individual in the team. Cooperative optimization
is a newly proposed general method for attacking hard optimization problems
inspired by cooperation principles in team playing. It has an established
theoretical foundation and has demonstrated outstanding performances in solving
real-world optimization problems. With some general settings, a cooperative
optimization algorithm has a unique equilibrium and converges to it with an
exponential rate regardless initial conditions and insensitive to
perturbations. It also possesses a number of global optimality conditions for
identifying global optima so that it can terminate its search process
efficiently. This paper offers a general description of cooperative
optimization, addresses a number of design issues, and presents a case study to
demonstrate its power.
