As with all "classic algorithms," its output was deterministic: it produced the same result for the same input every time. It would always finish, and it always produced the optimal, correct result.

Addressing the importance of the algorithm design process, Deterministic Operations Research focuses on the design of solution methods for both continuous and discrete linear optimization problems.

Additionally, deterministic algorithms for root finding, based on adaptations of Graeffe transforms, have been refined to overcome previous limitations, ensuring reliable extraction of polynomial ...

Due to the NP -hardness of many machine learning problems such as clustering, decision tree, and neural network, one primary belief is that solving ML problems to global optimality is computationally ...