METHOD FOR SOLVING NONLINEAR GOAL PROGRAMMING WITH INTERVAL-COEFFICIENTS USING GENETIC ALGORITHM

Traditional formulations on reliability optimization problems have ass umed that the coefficients of models are known as fixed quantities and reliability design problem is treated as deterministic optimization p roblems. Because that the optimal design of system reliability is reso lved in the same stage of overall system design, model coefficients ar e highly uncertainty and imprecision during design phase and it is usu ally very difficult to determine the precise values for them. However, these coefficients can be roughly given as the intervals of confidenc e. In this paper, we formulated reliability optimization problem as no nlinear goal programming with interval coefficients and develop a gene tic algorithm to solve it. The key point is how to evaluate each solut ion with interval data. We give a new definition on deviation variable s which take interval relation into account. Numerical example is give n to demonstrate the efficiency of the proposed approach. (C) 1997 Els evier Science Ltd.