Optimization algorithms and
software. Faster and more effective algorithms and software for
nonlinear, mixed-integer, and linear programming.
infeasibility in optimization. Ways of reaching a feasible solution
more quickly for nonlinear and mixed-integer programs, and of analyzing
infeasible optimization models. Spin-off applications from algorithms for
assistants. Automated tools for analyzing and debugging optimization
models. For example, one tool analyzes the shape of nonlinear functions
and regions to help select the correct solver.