Effectively Tackling Reinsurance Problems by Using Evolutionary and Swarm Intelligence Algorithms

Effectively Tackling Reinsurance Problems by Using Evolutionary and Swarm Intelligence Algorithms

This paper is focused on solving different hard optimization problems that arise in the field of insurance and, more specifically, in reinsurance problems. In this area, the complexity of the models and assumptions considered in the definition of the reinsurance rules and conditions produces hard black-box optimization problems (problems in which the objective function does not have an algebrai...

Tackling Dynamic Problems with Multiobjective Evolutionary Algorithms

In this chapter, we discuss the use of multiobjective evolutionary algorithms (MOEAs) for solving single-objective optimization problems in dynamic environments. Specifically, we investigate the consideration of a second (artificial) objective, with the aim of maintaining greater population diversity and adaptability. The paper suggests and compares a number of alternative ways to express this ...

Swarm Intelligence and Evolutionary Algorithms: Performance versus speed

The popularity of metaheuristics, especially Swarm Intelligence and Evolutionary Algorithms, has increased rapidly over the last two decades. Numerous algorithms are proposed each year, and progressively more novel applications are being found. However, different metaheuristics are often compared by their performance on problems with an arbitrarily fixed number of allowed function calls. There ...

Computational complexity of evolutionary algorithms, hybridizations, and swarm intelligence

ANN Models Optimized using Swarm Intelligence Algorithms

Artificial Neural Network (ANN) has found widespread application in the field of classification. Many domains have benefited with the use of ANN based models over traditional statistical models for their classification and prediction needs. Many techniques have been proposed to arrive at optimal values for parameters of the ANN model to improve its prediction accuracy. This paper compares the i...