Abstract:
Many business decision problems involve multiple objectives and can thus be
described by multiple objective linear programming (MOLP) models. When a MOLP
problem is being formulated, the parameters of objective functions and constraints
are normally assigned by experts. In most real situations, the possible values of these
parameters are imprecisely or ambiguously known to the experts. Therefore, it would
be more appropriate for these parameters to be represented as fuzzy numerical data that
can be represented by fuzzy numbers. In this paper, a new approximate algorithm is
developed for solving fuzzy multiple objective linear programming (FMOLP) problems
involving fuzzy parameters in any form of membership functions in both objective functions
and constraints. A detailed description and analysis of the algorithm are supplied.
In addition, an example is given to illustrate the approximate algorithm.
