Your Search Results

Use this resource - and many more! - in your textbook!

AcademicPub holds over eight million pieces of educational content for you to mix-and-match your way.

Experience the freedom of customizing your course pack with AcademicPub!
Not an educator but still interested in using this content? No problem! Visit our provider's page to contact the publisher and get permission directly.

Parallel Library of Multi-objective Evolutionary Algorithms

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

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

Description

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.