code: def base_model(n,c,t):
      
      from atsp import mtz_strong
      model = mtz_strong(n,c)     # model for minimizing cost
      x,u = model.data
  
      # some auxiliary information
      C = model.addVar(vtype="C", name="C")       # for computing solution cost
      T = model.addVar(vtype="C", name="T")       # for computing solution time
  
      model.addCons(T == quicksum(t[i,j]*x[i,j] for (i,j) in x), "Time")
      model.addCons(C == quicksum(c[i,j]*x[i,j] for (i,j) in x), "Cost")
  
      model.data = x,u,C,T
      return model
docs: base_model: mtz model for the atsp, prepared for two objectives
      Loads two additional variables/constraints to the mtz model:
          - C: sum of travel costs
          - T: sum of travel times
      Parameters:
          - n: number of cities
          - c,t: alternative edge weights, to compute two objective functions
      Returns list of candidate solutions