An Improved Nondominated Sorting Algorithm
This paper presents a new procedure for the nondominated sorting with constraint handling to be used in a multiobjective evolutionary algorithm. The strategy uses a sorting algorithm and binary search to classify the solutions in the correct level of the Pareto front. In a problem with objective fun...
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| Veröffentlicht in: | International journal of natural computing research 2012-10, Vol.3 (4), p.20-42 |
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| creator | da Cruz, André R |
| description | This paper presents a new procedure for the nondominated sorting with constraint handling to be used in a multiobjective evolutionary algorithm. The strategy uses a sorting algorithm and binary search to classify the solutions in the correct level of the Pareto front. In a problem with objective functions, using solutions in the population, the original nondominated sorting algorithm, used by NSGA-II, has always a computational cost of in a naïve implementation. The complexity of the new algorithm can vary from in the best case and in the worst case. A experiment was executed in order to compare the new algorithm with the original and another improved version of the Deb’s algorithm. Results reveal that the new strategy is much better than other versions when there are many levels in Pareto front. It is also concluded that is interesting to alternate the new algorithm and the improved Deb’s version during the evolution of the evolutionary algorithm. |
| doi_str_mv | 10.4018/jncr.2012100102 |
| format | Article |
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| ispartof | International journal of natural computing research, 2012-10, Vol.3 (4), p.20-42 |
| issn | 1947-928X 1947-9298 |
| language | eng |
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| source | ProQuest Central UK/Ireland; Alma/SFX Local Collection; ProQuest Central |
| subjects | Algorithms Computational efficiency Evolution Evolutionary algorithms Genetic algorithms Mathematical models Pareto optimality Sorting algorithms Strategy |
| title | An Improved Nondominated Sorting Algorithm |
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