Vol 6 No 1 (2011)

The AID Method for Global Optimization

Mahamed G.H. Omran
Gulf University for Science and Technology
Fred Glover
Department of Mathematics, Simon Fraser University
Published May 30, 2011
  • Metaheuristics,
  • Global Optimization,
  • Continuous Function Minimization,
  • Scatter
How to Cite
Omran, M. G., & Glover, F. (2011). The AID Method for Global Optimization. Algorithmic Operations Research, 6(1), Pages 20 - 28. Retrieved from https://journals.lib.unb.ca/index.php/AOR/article/view/12696


An Alternating Intensification/Diversification (AID) method is proposed to tackle global optimization problems, focusing here on global function minimization over continuous variables. Our method is a local search procedure that is particularly easy to implement, and can readily be embedded as a supporting strategy within more sophisticated methods that make use of population-based designs. We perform computational tests comparing the AID method to 20 other algorithms, many of them representing a similar or higher level of sophistication, on a total of 28 benchmark functions. The results show that the new approach generally obtains good quality solutions for unconstrained global optimization problems, suggesting the utility of its underlying notions and the potential value of exploiting its multiple avenues for generalization.