The purpose of this study is to develop a nesting algorithm, using a genetic algorithm to optimize nesting order, and modified No Fit Polygon(NFP) methodology to place parts with the order generated from the previous genetic algorithm. Various genetic algorithm techniques, which have thus far been applied to the Travelling Salesman Problem, were tested. The partially mapped crossover method, the inversion method for mutation, the elitist strategy, and the linear scaling method of fitness value were selected to optimize the nesting order. A modified NFP methodology, with improved searching capability for non-convex polygon, was applied repeatedly to the placement of parts according to the order generated from previous genetic algorithm. Modified NFP, combined with the genetic algorithms that have been proven in TSP, were applied to the nesting problem. For two example cases, the combined nesting algorithm, proposed in this study, shows better results than that from previous studies.