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Binary Ant Colony Optimization for Subset Problems

  • Nadia Abd-AlsabourEmail author
Chapter
Part of the Studies in Computational Intelligence book series (SCI, volume 592)

Abstract

Many optimization problems involve selecting the best subset of solution components. Besides, many other optimization problems can be modelled as a subset problem. This chapter focuses on developing a new framework in ant colony optimization (ACO) for optimization problems that require selection rather than ordering with an application to feature selection for regression problems as a representative for subset problems. This is addressed through three steps that are: explaining the main guidelines of developing an ant algorithm, demonstrating different solution representations for subset problems using ACO algorithms, and proposing a binary ant algorithm for feature selection for regression problems.

Keywords

Ant colony optimization Binary ant colony optimization (BACO) Subset problems Feature selection 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  1. 1.Cairo University CairoCairoEgypt

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