Azadeh Hassanpour

This paper optimizes wheat breeding programs using an evolutionary algorithm, achieving higher genetic gain and diversity while maintaining a fixed budget.

The paper compares selection strategies to improve genetic gain and reduce inbreeding over multiple generations using simulation software.

This paper introduces a framework for numerically optimizing breeding programs by maximizing a target function that combines genetic gain and diversity conservation, using stochastic simulations and kernel regression.