Algebraic and graphic comparison of crisp, interval and fuzzy approach to solving linear programming problems

In conventional teaching LP problems, all coefficients of a mathematic model are usually given exactly and an exact optimum can therefore be found. In practice, however, the limit values are often expressed vaguely and it is necessary to use relaxed capacity limits and a more appropriate concept of solving LP problems, especially the fuzzy method. The article presents a didactic proposal of how to familiarize business students with the idea of interval and fuzzy approaches. It suggests introducing the approaches to the students through illustration and comparison between algebraic and graphic solutions by means of oblique and orthographic projection. For that reason, a common example with just two structure variables is solved and depicted. The paper will use triangular fuzzy numbers to facilitate the explanation. Our own formulas for interval optimum are derived and Bellman and Zadeh ' s min-max operator for fuzzy optimum is used. The graphic solutions are depicted and compared.