Many-Objective Evolutionary Optimisation

نویسندگان

  • Francesco di Pierro
  • Soon-Thiam Khu
  • Dragan A. Savic
چکیده

Many-objective evolutionary optimisation is a recent research area that is concerned with the optimisation of problems consisting of a large number of performance criteria using evolutionary algorithms. Despite the tremendous development that multi-objective evolutionary algorithms (MOEAs) have undergone over the last decade, studies addressing problems consisting of a large number of objectives are still rare. The main reason is that these problems cause additional challenges with respect to low-dimensional ones. This chapter gives a detailed analysis of these challenges, provides a critical review of the traditional remedies and methods for the evolutionary optimisation of many-objective problems and presents the latest advances in this field.

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تاریخ انتشار 2009