A fuzzy nonlinear goal programming approach is presented for solving multiobjective optimization problems involving vague and imprecise information. Several computational models, including simple additive, weighted additive, and preemptive priority models, are given for the numerical solution of the problem. The methodologies are illustrated with the help of two structural optimization problems involving multiple goals. The solution of the first example is obtained using a graphical procedure whereas the second example is solved using nonlinear programming techniques. Linear membership functions are used in the numerical work for simplicity. The methodologies presented in this work aid in the preliminary design of structural systems involving imprecise and vague information about the goals and/or constraints.
ASJC Scopus subject areas
- Aerospace Engineering