  Paper provides a method for solving the reverse Monge-Kantorovich transport
problem (TP). It allows to accumulate positive decision-taking experience made
by decision-taker in situations that can be presented in the form of TP. The
initial data for the solution of the inverse TP is the information on orders,
inventories and effective decisions take by decision-taker. The result of
solving the inverse TP contains evaluations of the TPs payoff matrix elements.
It can be used in new situations to select the solution corresponding to the
preferences of the decision-taker. The method allows to gain decision-taker
experience, so it can be used by others. The method allows to build the model
of decision-taker preferences in a specific application area. The model can be
updated regularly to ensure its relevance and adequacy to the decision-taker
system of preferences. This model is adaptive to the current preferences of the
decision taker.
