Awards recognize foundational research that helped shape mixed-integer and nonlinear optimization—and reflect the company’s deep scientific roots.

Abstract: The problem of time-dependent nonlinear equality-constraint programming (TDNECP) is a hot topic in various scientific and engineering fields. In this paper, the problem-solving of TDNECP is ...

Abstract: The branch and bound (BB) algorithm is widely used to obtain the global solution of mixed-integer linear programming (MILP) problems. On the other hand, when the traditional BB structure is ...

Support vector regression can predict numeric values effectively, and this article shows how to implement and train a kernel SVR model in C# using stochastic sub-gradient descent.

PyAutoFit is a Python based probabilistic programming language for model fitting and Bayesian inference of large datasets. The basic PyAutoFit API allows us a user to quickly compose a probabilistic ...

Clarkson University researchers have developed an artificial intelligence tool that can uncover the mathematical equations ...

Developers are increasingly relying on large language models (LLMs) for everyday computing tasks such as fixing bugs, ...

Combinatorial optimization problems are often encountered in real-world applications, including logistics, scheduling and ...

Learning to program in C on an online platform can provide structured learning and a certification to show along with your resume. Learning C can still be useful in 2026, especially if you want to ...

In recent years, the frequency of weather-related natural disasters—cyclones, torrential rains, floods—has increased as a consequence of global warming. These disasters cause billions of dollars in ...

algorithms, namely iterative optimizers and more specialized model trainers. General optimizers are organized into direct search and gradient-based optimization. Specialized algorithms for linear ...