Genetic Algorithm for solving flow problems in a Stochastic-flow Network under Budget Constraints

Abstract

The system reliability (R_d,c) calculation is based on the generation of all the lower boundary points for the given demand, d, such that the total transmission cost is less than or equal to c (budget). This generation of the lower boundary points is based on finding all feasible solutions to the flow vector, F. The number of feasible solutions cannot be anticipated. Thus, a genetic algorithm is useful for solving this problem. Therefore, this paper presents a genetic algorithm to generate all feasible solutions to the flow vector, F, and then calculate R_d,c. The algorithm is applied to two problem models. In the first, each arc of a flow network has several capacities and may fail. In the second, both the arc and node have several capacities and may fail. The results show that the algorithm is efficient at solving a flow problem and is useful for calculating R_d,c.