Write down the Linear Program (LP) relaxation of an IP Plot the graphical representation of an IP and find the optimal solution Understand the relationship between optimal solution of an IP and the ...

Looking for good code examples for LeetCode problems? You’re in luck! Lots of people share their solutions online, especially ...

Optimization techniques have become a core tool for solving complex problems across diverse fields such as engineering design, economic planning, and scientific discovery. When tackling real-world ...

$$ \begin{array}{ll} \underset{x \in \mathbb{R}^n}{\min} \quad & \langle c, x \rangle \\ \text{s.t.} \quad & L \leq A x \leq U, \\ & l \leq x \leq u . \end{array ...

Finding the right book can make a big difference, especially when you’re just starting out or trying to get better. We’ve ...

Mathematics, like many other scientific endeavors, is increasingly using artificial intelligence. Of course, math is the ...

Neuromorphic computers modeled after the human brain can now solve the complex equations behind physics simulations — something once thought possible only with energy-hungry supercomputers. The ...

Like many of us, [Tim]’s seen online videos of circuit sculptures containing illuminated LED filaments. Unlike most of us, however, he went a step further by using graph theory to design glowing ...

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with pseudo-inverse training implemented using JavaScript. Compared to other training techniques, such as ...

NPR's Short Wave talks about babies' perceptions of rhythm, how sleep may help us solve puzzles and why snakes may be able to fast so long.

Real-world optimization problems often require an external “modeling engine” that computes fitnesses or data that are then input to an objective function. These programs often have much longer ...

Abstract: Unit commitment (UC) problems are typically formulated as mixed-integer programs (MIP) and solved by the branch-and-bound (B&B) scheme. The recent advances in graph neural networks (GNN) ...