Considering that differential evolution algorithm (DE) is sensitive to the selection of control parameters and population diversity's decrease leads to the loss of power as DE is applied in heat exchanger network (HEN), a weighted differential evolution algorithm (WDE) is applied in this study. Effectiveness of the algorithm has been proved in continuous variable optimization. This study applies it in mixed integer nonlinear programming problems of HEN without controlling parameters. Three cases ranging from small to medium testify the effectiveness of WDE. By setting up equal mutation factor and analyzing its distribution, we explore WDE's optimization mechanism which provides reference for algorithm improvements.