We compare two implementation schemes of local search in hybrid evolutionary multiobjective optimization algorithms. One is based on the weighted sum of multiple objectives, and the other is based on Pareto dominance. These two implementation schemes are compared with each other through computational experiments on a knapsack problem and a flowshop scheduling problem. We also examine a simple modification of the weighted sum-based scheme.