Abstract
The inclusion of reinforcements within the soil mass increases the bearing capacity and reduces the settlement of soil foundation. To achieve optimum bearing capacity with a minimum cost of foundation is a conflicting optimization problem. In this chapter, nondominated sorting genetic algorithm (NSGA-II), a multi-objective optimization algorithm is used to find out the maximum bearing capacity factor with a minimum cost of the foundation. A design methodology considering both the pull out and rupture failure of geosynthetic reinforcement available in the literature is used. The results of the conflicting objectives are presented in terms of the Pareto-optimal set. The NSGA-II is found to be very efficient in identifying the Pareto-optimal set of the reinforced soil foundation. The implementation issue of NSGA-II parameters is discussed. A parametric study is also made to identify the important soil and reinforcement parameters in achieving the Pareto-optimal solution.
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