Genetic Algorithm Approach to Solve Integer Nonlinear Programming Problem in Reliability Optimization

摘要

In the recent years, different types of optimization techniques have been advanced rapidly and applied widely to solve several optimization problems. These advancements are depends on both the upgrading progress of modern computer technologies and that of optimization process for large scale system. The most important optimization problem in reliability optimization is redundancy allocation problem. However, these problems have always been solved in the precise setup. In this paper, the reliability of each component is considered to be imprecise. The goal of this paper is to solve the redundancy allocation problem that maximize the overall system reliability subject to the given resource constraints. This impreciseness has been represented by interval number. This type of problem has been formulated as an interval valued constrained optimization problem. Then the constrained optimization problem has been transformed into unconstrained one by penalty function technique then solved by Genetic Algorithm. Finally, to illustrate the methodology, a numerical example has been presented and solved for illustration purpose.