Evolutionary Multiobjective Optimization with Gaussian Process Models - Brossura

Mlakar, Miha

Brossura

ISBN 10: 365975935X ISBN 13: 9783659759352

Casa editrice: LAP LAMBERT Academic Publishing, 2015

Riassunto

This book focuses on the field of surrogate-model-based multiobjective evolutionary optimization. It describes the sate-of-the-art concepts and methods, presents various optimization problems and describes current challenges. The main contributions are done for the optimization problems, where solutions are presented with uncertainty. To compare solutions under uncertainty and improve the optimization results the new relations for comparing solutions under uncertainty are defined. These relations reduce the possibility of incorrect comparisons due to the inaccurate approximations. The relations under uncertainty are then used in the new surrogate-model-based multiobjective evolutionary algorithm called GP-DEMO. The algorithm is thoroughly tested on benchmark and real-world problems and the results show that GP-DEMO, in comparison to other multiobjective evolutionary algorithms, produces comparable results while requiring fewer exact evaluations of the original objective functions.

Dettagli dell?edizione

• Editore: LAP LAMBERT Academic Publishing
• Data di pubblicazione: 2015
• ISBN 10: 365975935X
• ISBN 13: 9783659759352
• Rilegatura: Copertina flessibile
• Lingua: Inglese
• Numero di pagine: 116
• Contatto del produttore: non disponibile