strained multi-objective optimization using constrained non-dominated sorting combined with an improved hybrid multi-objective evolutionary algorithm", Engineering Optimization This document includes:(1) The visual representation of the Pareto fronts obtained by cMOEA/H and the baseline algorithm cMOEA/H-CD (Figure S1 -Figure S3). ( 2) The comparison of the convergence property between cMOEA/H and cMOEA/H-CD (Figure S4). (3) The general cMOEA/D framework adopted by four cMOEA/Ds (cMOEA/D-CD, cMOEA/D-EC, cMOEA/D-P and cMOEA/D-SR) (Algorithm S1). (4) The box plots of I hv obtained by NSGA-II, cMOEA/H, cMOEA/D-CD, cMOEA/D-EC, cMOEA/D-P and cMOEA/D-SR in solving each test instance over thirty runs (Figure S5). (5) Computational complexity analysis of NSGA-II, cMOEA/H and cMOEA/D.
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