caa a22 4500 605468389 CHVBK 20210128100316.0 cr unu---uuuuu 210128e20150101xx s 000 0 eng 10.1007/s00500-014-1239-3 doi (NATIONALLICENCE)springer-10.1007/s00500-014-1239-3 Multiobjective evolutionary algorithm based on decomposition for 3-objective optimization problems with objectives in different scales [Elektronische Daten] [Álvaro Rubio-Largo, Qingfu Zhang, Miguel Vega-Rodríguez] In Multiobjective Optimization problems the objective functions may have different scales, which leads to a neglecting of one or more objective functions. The most common-used way in the literature to solve this drawback is to normalize the objective space; however, a set of uniformly distributed solutions in the normalized objective space may not be uniformly distributed in the original objective space with more than two objective functions. In this work, we present an improved version of the Multiobjective Evolutionary Algorithm based on Decomposition (MOEA/D) which incorporates a new aggregation technique based on the Normal Boundary Intersection approach and the Tchebycheff approach (MOEA/D-NBI) for solving 3-objective optimization problems with different scales of objectives. Springer-Verlag Berlin Heidelberg, 2014 Multiobjective optimization nationallicence Evolutionary algorithms nationallicence Pareto optimally nationallicence Normal Boundary Intersection nationallicence Rubio-Largo Álvaro Department of Computer and Communications Technologies, University of Extremadura, Cáceres, Spain aut Zhang Qingfu Department of Computer Science, City University of Hong Kong, Hong Kong, China aut Vega-Rodríguez Miguel Department of Computer and Communications Technologies, University of Extremadura, Cáceres, Spain aut Soft Computing Springer Berlin Heidelberg 19/1(2015-01-01), 157-166 1432-7643 19:1<157 2015 19 500 https://doi.org/10.1007/s00500-014-1239-3 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00500-014-1239-3 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Rubio-Largo Álvaro Department of Computer and Communications Technologies, University of Extremadura, Cáceres, Spain aut NATIONALLICENCE 700 1- Zhang Qingfu Department of Computer Science, City University of Hong Kong, Hong Kong, China aut NATIONALLICENCE 700 1- Vega-Rodríguez Miguel Department of Computer and Communications Technologies, University of Extremadura, Cáceres, Spain aut NATIONALLICENCE 773 0- Soft Computing Springer Berlin Heidelberg 19/1(2015-01-01), 157-166 1432-7643 19:1<157 2015 19 500