Algorithm Configurations of MOEA/D with an Unbounded External Archive

27 Jul 2020 Lie Meng Pang Hisao Ishibuchi Ke Shang

In the evolutionary multi-objective optimization (EMO) community, it is usually assumed that the final population is presented to the decision maker as the result of the execution of an EMO algorithm. Recently, an unbounded external archive was used to evaluate the performance of EMO algorithms in some studies where a pre-specified number of solutions are selected from all the examined non-dominated solutions... (read more)

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