ML, Optimisation, Convex Optimization, Price Optimization.
of both bounds and constraints. Hence we are using SLSQP, which supports the use of both the bounds and constraints for optimisation. Results of convex optimisation The optimisation was run for a total of 3 iterations. Based on this the objective function has returned a value of -6.6 mil (i.e.