A Linearization Technique for Solving Chance-Constrained Goal Programming Problems

Typically, due to transformation of a probabilistic constraint into an equivalent deterministic form (EDF), a nonlinear constrained generates. The effectiveness of a linearly approximated goalprogramming (GP) model representing such a nonlinear goal program is the topic of this article. The goodness and efficiency of a proposed iterative solution technique for solving this special class of nonlinear goal programming (NGP) problem in a finite number of iterations is discussed. The proposed computer algorithm is tested and verified by experimenting on classical chance constrained goal programming (CCGP) problems.

Keywords:

Linearization , Chance Constrained Programming , Goal programming , and Nonlinear Programming