title: Pulp Optimization Problem - Constraint Problems
body: <p>I'm creating an optimization function with PuLP to optimize a portfolio. I have a list of assets that each have one of the following Liquidity Levels [1, 2, 3].</p>
  <p>I am attempting to create a constraint that at least 20% of the portfolio needs to have Level 1 liquidity.</p>
  <p>I have created a dictionary (liquidity) that has saved the {'Asset':Level} and am attempting to create the constraint with this and the asset variable (asset_vars), which is a LpVariable.</p>
  <p><code>asset_vars = pl.LpVariable.dicts(&quot;Assets&quot;, asset_list,lowBound=0, upBound=1, cat='Integer')</code></p>
  <p><code>prob += pl.lpSum([liquidity[f] * asset_vars[f] for f in asset_vars]) &gt;= ?</code></p>
  <p>I know my setup now is not close to what I would need to do, however, I am having difficulty finding / coming up with a solution.</p>