This special session aims to attract the most recent advances produced in the following topics, including but not limited to:

• Management of diversity in the decision space in single-objective population-based metaheuristics

• Management of diversity in multi-objective population-based metaheuristics, both in the decision and/or objective space

• Relation between diversity management and quality of attained results

• Restarting mechanisms

• Population Sizing Schemes

• Methods based on mating restrictions

• Diversity-based operators: parent-centric vs. mean-centric operators and its relation to diversity, adaptive operators, etc.

• Niching and crowding mechanisms

• Multi-objective methods for promoting diversity in single-objective optimization:

  • Mechanisms that transform a constrained single-objective problem into an unconstrained multi-objective problem

  • Diversity-based multi-objective approaches: diversity considered as auxiliary objective functions, encoding-independent measures, genotypic and phenotypic measures, behavioral (diversity and novelty) measures, etc.

  • Multi-objectivization by decomposition or aggregation

• Methods based on complex population structures:

  • Island-based models and distributed algorithms

  • Cellular approaches

  • Segregation techniques

• Clustering techniques

• Management of diversity in memetic algorithms

• Diversity measures for specific branches of EC such as Genetic Programming, Neuroevolution, and EAs for constrained optimization.

• Diversity measures in combinatorial and continuous spaces

• Premature convergence detection

• Real-world applications requiring the application of diversity preservation mechanisms for being successfully solved