NFL Football

Combinatorial optimization problems arise across logistics, scheduling, and engineering, and C++ remains a language of choice when performance matters. This lecture takes a practical look at solving such problems in C++, using the Electric Vehicle Routing Problem as a running example. We begin with an exact solver, formulating the problem as a mixed-integer program and trying to solve it through GLPK's C API directly from C++. Exact methods, however, quickly hit their limits on real-world instances. The second half of the talk turns to metaheuristics: how they are designed, why C++ is particularly well suited for implementing them, and what design choices matter most in practice. We'll walk through a concrete implementation, touching on data structures for fast neighborhood evaluation, generic algorithm design with templates, and the performance considerations that separate a prototype from a production-ready solver. The goal is not to advocate for one approach over another, but to show how C++ supports the full spectrum of optimization techniques.

Combinatorial optimization problems arise across logistics, scheduling, and engineering, and C++ remains a language of choice when performance matters. This lecture takes a practical look at solving such problems in C++, using the Electric Vehicle Routing Problem as a running example. We begin with an exact solver, formulating the problem as a mixed-integer program and trying to solve it through GLPK's C API directly from C++. Exact methods, however, quickly hit their limits on real-world instances. The second half of the talk turns to metaheuristics: how they are designed, why C++ is particularly well suited for implementing them, and what design choices matter most in practice. We'll walk through a concrete implementation, touching on data structures for fast neighborhood evaluation, generic algorithm design with templates, and the performance considerations that separate a prototype from a production-ready solver. The goal is not to advocate for one approach over another, but to show how C++ supports the full spectrum of optimization techniques.

Dodgeball is back again! If you’ve been wanting to come out, this is an easy one to join. We’ll be playing for about 1.5 to 2 hours, you do not need to bring any equipment, and no experience is needed. We use a specific set of rules and equipment to make the games run better and keep them fun for everybody, not just people who already know how to play. If it rains, the event will be canceled.

**Important time note:** Please plan on arriving between 5:30 and 6:00 as the elevators lock after 6 and you'll need to message us and we'll need to come get you. The building address is 4450 Bridge Park The entrance is 6620 Mooney St, Suite 400 You will need to scan your ID at the door to get a visitor badge. **Abstract** Like it or not, AI agents are now capable of turning a quickly written paragraph of requirements into a pull request that is ready to be integrated into real-world production applications and it's now our responsibility to make sure AI doesn't go rogue and take down prod - or corrupt our data by misunderstanding the requirements or our existing schemas. In this session we'll explore strategies to protect our codebases through unit and integration testing, documentation, and code review along with additional ways of providing context and guard rails to our AI agents as they carry out the work we've assigned them to do. By the time we're done, you'll have a firm grasp of the problem and understand some helpful options for protecting your codebase from vibe coding mishaps getting YOLOed into prod. **YouTube Link** https://youtube.com/live/BltmWMH1zG0?feature=share