Neuro-Fuzzy Programming to Finding Fuzzy Multiple Objective Linear Programming Problems

A neural network for solving fuzzy multiple
objective linear programming problems is proposed in
this paper. The distinguishing features of the proposed
Neural network are that the primal and dual problems
can be solved simultaneously, all necessary and sufficient
optimality conditions are incorporated, and no penalty
parameter is involved. we prove strictly an important
theoretical result so that, for an arbitrary initial point,
the trajectory of the proposed network does converge to
the set of its equilibrium points, regardless of whether a
multiple objective linear programming problem has
unique or infinitely many optimal solutions. Numerical
simulation results also show that the proposed network
is feasible and efficient. In addition, a general method for
transforming nonlinear programming problems into
unconstrained problems is also proposed.