As a collective group, scientists would probably vote slightly left of the centre, be more liberal in their political and social views and would be genuinely concerned about inequalities in society. Scientists rarely use the word ‘elite’ without some apologetic justification, yet we constantly speak about selection through excellence—and hence exclusion of a nonelite—without any blushes. Althou...

NSGA ( [5]) is a popular non-domination based genetic algorithm for multiobjective optimization. It is a very effective algorithm but has been generally criticized for its computational complexity, lack of elitism and for choosing the optimal parameter value for sharing parameter σshare. A modified version, NSGAII ( [3]) was developed, which has a better sorting algorithm , incorporates elitism...

Elitism and sharing are two mechanisms that are believed to improve the performance of an evolutionary multi-criterion optimiser. The relative performance of the two most popular ranking strategies is largely unknown. Using a new empirical inquiry framework, this report studies the effect of elitism, sharing, and ranking design choices using a benchmark suite of two-criterion problems. Performa...

Abstract The Fields Medal, often referred as the Nobel Prize of mathematics, is awarded to no more than four mathematicians under age 40, every 4 years. In recent years, its conferral has come scrutiny math historians, for rewarding existing elite rather original goal elevating under-represented mathematicians. Prior studies elitism focus on citational practices while a characterization structu...

Élitisme et Dominance Stochastique Résumé La dominance stochastique est traditionnellement associée à la mesure du risque et de l'inégalité et repose sur la concavité de la fonction d'utilité. Nous prétendons que l'approche en terme de dominance stochastique a des implications qui vont au-delà de la mesure du risque et de l'inégalité pour peu que l'on procède à certains ajustements. Nous appliq...

In recent years the genetic algorithm community has shown a growing interest in studying dynamic optimization problems. Several approaches have been devised. The random immigrants and memory schemes are two major ones. The random immigrants scheme addresses dynamic environments by maintaining the population diversity while the memory scheme aims to adapt genetic algorithms quickly to new enviro...