Intelligent Optimization Strategies in Uncertain and Dynamic Environments

In recent years, biological and natural processes have been increasingly influencing methodologies in science and technology. In particular, the role played by the cooperation among individuals is being studied more frequently and profoundly in diverse areas of knowledge.
We present here a multiagent decentralized strategy for dynamic optimization problems where a population of cooperative agents and solutions are used to deal with the moving peaks problem. We focus on cooperation and diversity mechanisms, and we study how different alternatives affect the performance of the strategy.