Solving possibilistic linear programming problems
In a possibilistic linear program (LP) there are uncertain coefficients determined by possibilistic distributions in contrast to probabilistic distributions for stochastic LP. In this paper a solution procedure for possibilistic LP with inequality constraints is presented. A standard form of a possibilistic LP is defined, then the solution involves specifying the possibility distribution for the objective function and then determining a compromise solution for the decision variables. Two different definitions of possibility distribution for the objective function are considered. It is shown that for certain programs they supply the same results. Non- standard problems are also discussed by presenting and solving on example of a non-standard problem. General suggestions on how to solve any non- standard problem are given.
scientific article; zbMATH DE number 4099032