A technique for finding MINSUM and MINMAX solutions to multi-criteria decision problems, called Multi Objective Dynamic Programming, capable of handling a wide range of linear, nonlinear, deterministic and stochastic multi-criteria decision problems, is presented and illustrated. Multiple objectives are considered by defining an adjoint state space and solving a (N + 1) terminal optimisation problem. The method efficiently generates both individual (criterion) optima and multiple criteria solutions in a single pass. Sensitivity analysis on weights over the various objectives is easily performed.