Abstract: To address the challenges posed by non-convex optimization in path planning for intelligent vehicles using numerical optimization techniques, this study introduces a combined approach ...

In the era of A.I. agents, many Silicon Valley programmers are now barely programming. Instead, what they’re doing is deeply, deeply weird. Credit...Illustration by Pablo Delcan and Danielle Del Plato ...

Programming is the backbone of modern technology, and understanding a programming languages list is essential for developers, students, and tech enthusiasts. In 2026, Python leads AI and data science ...

This study develops a unified framework for optimal portfolio selection in jump–uncertain stochastic markets, contributing both theoretical foundations and computational insights. We establish the ...

Genomics is playing an important role in transforming healthcare. Genetic data, however, is being produced at a rate that far outpaces Moore’s Law. Many efforts have been made to accelerate genomics ...

Texas-based healthcare data analytics company MedeAnalytics announced it is collaborating with fellow healthcare data analytics firms Socially Determined and Mathematica. The companies launched ...

This project implements a Dynamic Programming (DP) solution for optimal inventory control, inspired by fundamental principles in Dimitri Bertsekas's work on "Lessons from AlphaZero for Optimal, Model ...

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.jctc.5c00103.

Abstract: Differential Dynamic Programming (DDP) is an efficient tool for non-linear optimal problems. And DDP shows a characteristic of fast convergence. However, the traditional DDP cannot solve the ...

ABSTRACT: This study proposes a novel approach to optimizing individual work schedules for book digitization using mixed-integer programming (MIP). By leveraging the power of MIP solvers, we aimed to ...