Artículos regulares

 

Designing Minimal Sorting Networks Using a Bio-inspired Technique

 

Blanca C. López-Ramírez and Nareli Cruz-Cortés

 

Centro de Investigación en Computación, Instituto Politécnico Nacional, Mexico City, Mexico. bcelopez@gmail.com, nareli@cic.ipn.mx

 

Article received on 12/04/2014.
Accepted on 03/06/2014.

 

Abstract

Sorting Networks (SN) are efficient tools to sort an input data sequence. They are composed by a set of comparison-exchange operations called comparators. The comparators are a priori fixed for a determined input size. The comparators are independent of the input configuration. SN with a minimal number of comparators results in an optimal manner to sort data; it is a classical NP-hard problem studied for more than 50 years. In this paper we adapted a biological inspired heuristic called Artificial Immune System to evolve candidate sets of SN. Besides, a local strategy is proposed to consider the information regarding comparators and sequences to be ordered at a determined building stage. New optimal Sorting Networks designs for input sizes from 9 to 15 are presented.

 

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