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CEC
2011
IEEE

Accelerating convergence towards the optimal pareto front

12 years 11 months ago
Accelerating convergence towards the optimal pareto front
—Evolutionary algorithms have been very popular optimization methods for a wide variety of applications. However, in spite of their advantages, their computational cost is still a prohibitive factor in certain real-world applications involving expensive (computationally speaking) fitness function evaluations. In this paper, we depart from the observation that nature’s survival of the fittest is not about exact measures of fitness; rather it is about rankings among competing peers. Thus, by exploiting this natural tolerance for imprecision, we propose here a new, fuzzy granules-based approach for reducing the number of necessary function calls involving time consuming real-world problems. Our proposed approach is compared with respect to the standard NSGA-II, using the Set Coverage, Hypervolume and Generational Distance performance measures. Our results indicate that our proposed approach is a very promising alternative for dealing with multi-objective optimization problems invol...
Mohsen Davarynejad, Jafar Rezaei, Jos L. M. Vranck
Added 13 Dec 2011
Updated 13 Dec 2011
Type Journal
Year 2011
Where CEC
Authors Mohsen Davarynejad, Jafar Rezaei, Jos L. M. Vrancken, Jan van den Berg, Carlos A. Coello Coello
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