Solving complex optimization problems is central to many modern technologies, from logistics and financial modeling to chip ...

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.

Are you passionate about developing AI-based and quantum-inspired solutions for the next generation of sustainable energy systems? We are now looking for a fully funded Doctoral Researcher to work on ...

This transition moves inventory planning away from static safety stock rules toward more flexible policy structures that ...

Abstract: In this article, the problem of autonomous vehicle trajectory optimization with flexible final time is concerned under the consideration of stochastic disturbances. Stochastic differential ...

Your browser does not support the audio element. In 1952, Grace Hopper sat in front of a UNIVAC I and got tired of copying subroutine addresses by hand. Programmers ...

HiOp is an optimization solver for solving certain mathematical optimization problems expressed as nonlinear programming problems. HiOp is a lightweight HPC solver that leverages application's ...

Without resorting to dynamic programming, we determine the decumulation strategy for the holder of a defined contribution pension plan. We formulate this as a constrained stochastic optimal control ...

Abstract: Searching for symbolic models plays an important role in a wide range of domains such as neural architecture search and automatic program synthesis. Genetic programming is a promising ...

The U.S. military experienced logistics challenges with land-locked Afghanistan, but one of the last times it faced actively contested logistics was with the German submarine wolfpacks in World War II ...