A novel parallel decomposition algorithm is developed for large, multistage stochastic optimization problems. The method decomposes the problem into subproblems that correspond to scenarios. The ...

This course offers an introduction to mathematical nonlinear optimization with applications in data science. The theoretical foundation and the fundamental algorithms for nonlinear optimization are ...

Sequential optimality conditions for constrained optimization are necessarily satisfied by local minimizers, independently of the fulfillment of constraint qualifications. These conditions support the ...

On Monday the 2nd of December 2019, M.Sc. Paul Saikko will defend his doctoral thesis on Implicit Hitting Set Algorithms for Constraint Optimization. The thesis is a part of research done in the ...