An Improved Harmony Search Algorithm with Differential Mutation Operator

  • Authors:

  • Prithwish Chakraborty,;Gourab Ghosh Roy;Swagatam Das;Dhaval Jain;Ajith Abraham

  • Affiliations:

  • Department of Electronics and Telecommunication Engineering, Jadavpur University, Kolkata, India;Department of Electronics and Telecommunication Engineering, Jadavpur University, Kolkata, India;Department of Electronics and Telecommunication Engineering, Jadavpur University, Kolkata, India;Department of Electronics and Telecommunication Engineering, Jadavpur University, Kolkata, India;Machine Intelligence Research Labs (MIR Labs), Scientific Network for Innovation and Research Excellence, P.O. Box 2259 Auburn, Washington 98071-2259, USA. E-mail: ajith.abraham@ieee.org

  • Venue:
  • Fundamenta Informaticae - Swarm Intelligence
  • Year:
  • 2009

Quantified Score

Hi-index 0.00

Visualization

Abstract

Harmony Search (HS) is a recently developed stochastic algorithm which imitates the music improvisation process. In this process, the musicians improvise their instrument pitches searching for the perfect state of harmony. Practical experiences, however, suggest that the algorithm suffers from the problems of slow and/or premature convergence over multimodal and rough fitness landscapes. This paper presents an attempt to improve the search performance of HS by hybridizing it with Differential Evolution (DE) algorithm. The performance of the resulting hybrid algorithm has been compared with classical HS, the global best HS, and a very popular variant of DE over a test-suite of six well known benchmark functions and one interesting practical optimization problem. The comparison is based on the following performance indices - (i) accuracy of final result, (ii) computational speed, and (iii) frequency of hitting the optima.