Portfolio optimization with indicator function constraints in Cvxpy

I have the following portfolio optimization problem that I want to solve using Cvxpy:

However I am having troubles implementing the last constraint involving an indicator function. Any ideas on how to code that constraint? Also, if the constraint is not implementable in Cvxpy, is there any open-source solver that can deal with that kind of constraints? Thanks.

Paolo

I assume that $$w_i$$ is a continuous variable with $$0 \le w_i \le 1$$ and $$w_i^\text{start}$$ is a constant with $$0 \le w_i^\text{start} \le 1$$. You want to enforce $$|w_i-w_i^\text{start}| > 0 \implies |w_i-w_i^\text{start}| \ge 0.02.$$ You can introduce binary variables $$y_i^+$$ and $$y_i^-$$ and linear big-M constraints: \begin{align} 0.02 y_i^+ \le w_i - w_i^\text{start} &\le (1 - w_i^\text{start}) y_i^+ &&\text{for all i} \tag1 \\ 0.02 y_i^- \le w_i^\text{start} - w_i &\le (w_i^\text{start} - 0) y_i^- &&\text{for all i} \tag2 \end{align} Constraint $$(1)$$ enforces $$w_i - w_i^\text{start} > 0 \implies w_i - w_i^\text{start} \ge 0.02.$$ Constraint $$(2)$$ enforces $$w_i^\text{start} - w_i > 0 \implies w_i^\text{start} - w_i \ge 0.02.$$