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- W2916394031 abstract "Evolutionary algorithms can be used to solve the multi objective optimization problems in the field of machine learning. At the heart of many MOEAs exists a non dominated sorting procedure which sorts the individuals in the population into different groups (fronts) based on their fitness values. The non dominated sorting procedure can be divided into two sub problems. The first problem deals with finding the domination count (the number of individuals that dominates a particular solution) for entire set of the individuals in the population. The second sub problem aims on allocating the front to every individual in the population. This paper discusses the relationship between the domination count of an individual and the front allocated to it. Using these relations we propose the efficient algorithms for mapping an individual to its corresponding front." @default.
- W2916394031 created "2019-03-02" @default.
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- W2916394031 date "2018-12-01" @default.
- W2916394031 modified "2023-09-27" @default.
- W2916394031 title "EFA-An efficient algorithm for front allocation in non-dominated sorting" @default.
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- W2916394031 doi "https://doi.org/10.1109/isspit.2018.8642790" @default.
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