Think about Structural Fail State to Solve Geometric Reliability

The geometric reliability is usually applied in the structural analysis of the large projects. The structure-function is usually discrete or implicit. It is necessary to use penalty function to convert the constrained optimization problem into non-constrained optimization problem. We also analyze possible cheats of penalty in un-ultimate state (mostly happen in penalty safe sate). So it is proposed that only use structural fail regional variables by random sampling to solve the geometric reliability, obtain an non-constrained optimization problem and un-introduction penalty function. It proposed use discrete optimization (such as the GA, ACO, PSO and so on) to solve geometric reliability, the penalty is carried out on the variables in the safe state not in the structural fail and ultimate state. Through comparison of benchmarks from Monte-Carlo method, random sampling and GA in SFSCGR (Structural Fail State Calculation Geometric Reliability) and PSUUSCGR (Penalty Structural Un-Ultimate State Calculation Geometric Reliability), it is illustrated that SFSCGR is feasible, and it is very stable and accurate in geometric reliability solving.