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Parallel Library of Multi-objective Evolutionary Algorithms

By: Leon, C.; Segura, C.; Segredo, E.; Miranda, G.;

2009 / IEEE / 978-0-7695-3544-9


This item was taken from the IEEE Conference ' Parallel Library of Multi-objective Evolutionary Algorithms ' ULL::A-Team tool is a library that provides a skeleton to solve multi-objective optimization problems by applying evolutionary algorithms. In addition to providing sequential implementations of some of the best-known evolutionary algorithms, the skeleton provides great ¿exibility in obtaining parallel schemes. This ¿exibility is achieved by specifying con¿gurations that allow the execution of different parallel evolutionary models: homogeneous island-based model, heterogeneous island-based model and self-adaptive island-based model. To solve a particular problem, the user must specify all its properties by de¿ning a set of C++ classes. Additionally, the user can also incorporate new evolutionary algorithms to the tool. This work explains how to carry out this task using IBEA algorithm as a case study. In order to check the contribution of the new algorithm, the computational results obtained for the multi-objective knapsack problem are presented.