Algorithms: ENS

@article{ ens,
    author      = {Xingyi Zhang and Ye Tian and Ran Cheng and Yaochu Jin},
    title       = {An Efficient Approach to Nondominated Sorting
                   for Evolutionary Multiobjective Optimization},
    journal     = {IEEE Transactions on Evolutionary Computation},
    year        = {2015},
    volume      = {19},
    number      = {2},
    pages       = {201-213},
    publisher   = {IEEE},
    langid      = {english}
}

How to get an instance:

• ENS.getENS_SS() -- returns an instance of ENS with sequential insertion.
• ENS.getENS_BS() -- returns an instance of ENS with binary search insertion.

Both implementations require O(N) memory and have worst-case running time complexity O(MN^2). The ENS_SS version generally performs faster except for occasional M<=3. These algorithms are quite slow when the number of fronts is about 1. However, ENS_SS was the fastest algorithm on high-dimensional uniform inputs among all algorithms published on or before 2015.