A mathematical model of a unit cell of a ‘granular-pinned’ slope had been analyzed (Saha 2001) to predict the increased resistance of potential sliding mass of the ‘pinned’ slope due to higher shear strength and free-draining characteristics of the ‘granular-pin’ or column. The present investigation illustrates the effectiveness of a new generation optimization procedure, the genetic algorithms (GA), to find out the minimum Factor of Safety of virgin slope vis-à-vis reinforced slope. GA does not require problem specific knowledge for carrying out the search since it is a tool guided by stochastic principles instead of gradients. The objective function to be optimized in the two cases has been taken as the factor of safety expression of Bishop's simplified method (1960) for virgin slope and Saha's (2001) expression for reinforced slope. A specific stretch of vulnerable ‘Bhagirathi-Hooghly’ river bank (-the southern part of River Ganges- the major hydrodynamic system that formed the world's largest delta) has been chosen for the analysis. The study compares the results of prediction of failure susceptibility of river bank by directed grid-search in literature (Parua, 1992) with the present random search analysis. It emerged from the study that marked improvement in stability of such slopes could be achieved by granular-pinning that results in changing the potential virgin failure surface. Both gradual drawdown (GD) and instantaneous drawdown (ID) analysis exhibited marked improvement; though improvement in ID case, that is likely to govern in tidal deltaic zones, is about thrice than that obtained in GD case.