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October 2011 - December 2014
Publications
Publications (4)
Differential evolution (DE) is a powerful and simple algorithm for single-and multi-objective optimization. However, its performance is highly dependent on the right choice of parameters. To mitigate this problem, mechanisms have been developed to automatically control the parameters during the algorithm run. These mechanisms are usually a part of...
Differential evolution (DE) is a very powerful and simple algorithm for single-and multi-objective continuous optimization prob-lems. However, its success is highly affected by the right choice of pa-rameters. Authors of successful multi-objective DE algorithms usually use parameters which do not render the algorithm invariant with re-spect to rota...
Many multi-objective evolutionary algorithms rely on the non-dominated sorting procedure to determine the relative quality of individuals with respect to the population. In this paper we propose a new method to decrease the cost of this procedure. Our approach is to determine the non-dominated individuals at the start of the evolutionary algorithm...
Nondominated sorting and diversity estimation procedures are an essential part of many multiobjective optimization algorithms. In many cases these procedures are the com-putational bottleneck of the entire algorithm. We present the methods to decrease the cost of these procedures for multiobjective differential evolution (DE) algorithms. Our approa...
