A hybrid method for multi-objective shape optimization

  • Authors:

  • G. N. Sashi Kumar;A. K. Mahendra;A. Sanyal;G. Gouthaman

  • Affiliations:

  • Bhabha Atomic Research Centre, Trombay, Mumbai, India;Bhabha Atomic Research Centre, Trombay, Mumbai, India;Bhabha Atomic Research Centre, Trombay, Mumbai, India;Bhabha Atomic Research Centre, Trombay, Mumbai, India

  • Venue:
  • SEAL'10 Proceedings of the 8th international conference on Simulated evolution and learning
  • Year:
  • 2010

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Abstract

This paper introduces a hybrid shape optimization method (M-HYBRID) for multiple objectives (MO) using Genetic Algorithm (GA) and Ant Colony Optimization (ACO) in combination with a meshless computational fluid dynamics solver. It uses the reference point based approach to reach the required optimum. This method was found to converge faster than MO optimizer based on GA alone. The constraint on the handling large number of parameters with MO optimiser based on ACO is overcome in M-HYBRID. This hybrid optimizer is good contender when a global optimum is the target.