A Kind of Evolutionary Multi-Objective Optimization Algorithm Based on AIS

Ming Song Li

doi:10.4028/www.scientific.net/AMM.442.419

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 442A Kind of Evolutionary Multi-Objective...

A Kind of Evolutionary Multi-Objective Optimization Algorithm Based on AIS

Abstract:

Problem of multi-objective optimization based on Artificial Immune System (AIS) is an important research area of current evolutionary computing. Starting from the intelligent information processing mechanism of immune theory and the immune system itself, a kind of evolutionary multi-objective optimization algorithm based on AIS is proposed. Clonal selection, scattered crossover and hypermutation based on the learning mechanism are characteristics of the algorithm. Algorithm implements clonal selection according to the distribution of individuals in the objective space, which benefit obtaining Pareto optimal boundary distributed more widely and speed up the convergence. Compared with the existing algorithms, the algorithm has been greatly improved in convergence, diversity, and distribution of solutions.

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Periodical:

Applied Mechanics and Materials (Volume 442)

Pages:

419-423

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.442.419

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Online since:

October 2013

Authors:

Ming Song Li*

Keywords:

Artificial Immune System, Clonal Selection, Evolutionary Multi-Objective Optimization, Hypermutation, Scattered Crossover

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