Preliminary Study on the Performance of Multiobjective Evolutionary Algorithms with MNK-Landscapes
نویسندگان
چکیده
Epistasis and NK-Landscapes in the context of multiobjective evolutionary algorithms are almost unexplored subjects. Here we present an extension of Kauffman’s NK-Landscapes to multiobjective MNK-Landscapes in order to use them as a benchmark tool and as a mean to understand better the working principles of multiobjective evolutionary algorithms (MOEAs). In this work we present an elitist multiobjective random bit climber (moRBC) and compare its performance with NSGA-II and SPEA2, two elitist state of the art MOEAs.
منابع مشابه
Random Bit Climbers on Multiobjective MNK-Landscapes: Effects of Memory and Population Climbing
In this work we give an extension of Kauffman’s NKLandscapes to multiobjective MNK-Landscapes in order to study the effects of epistasis on the performance of multiobjective evolutionary algorithms (MOEAs). This paper focuses on the development of multiobjective random one-bit climbers (moRBCs). We incrementally build several moRBCs and analyze basic working principles of state of the art MOEAs...
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