Helio Barbosa: On Parallel Evolutionary Algorithms for Multilevel Optimization

Helio Barbosa Keynote Talk (CEC) at WCCI 2018 Abstract: The investigations in multilevel programming techniques are strongly motivated by real-world applications found in diverse areas such as economics, operations research, and engineering. Multilevel optimization problems are characterized by a hierarchical structure where in each level one or more agents (decision makers), controlling a partial set of the variables, seek to optimize, not necessarily in a cooperative way, their particular objective function, subject to given constraints, taking into account the decisions of agents in the upper, and often in the same, hierarchical level. Due to the complexity involved in solving these problems, evolutionary computation is a candidate tool to overcome the many challenges arising, such as non-convexity and non-differentiability, large number of variables and/or constraints, and mixed types of design variables. In this talk, ways to exploit the parallel nature of the evolutionary techniques will be discussed in order to construct distributed computational algoritms to tackle multilevel optimization problems.