Convex Relaxation Explorer

Deep dive into why GCS is computationally efficient and how it avoids the exponential complexity of traditional solvers. Convex Relaxation Explorer turns that idea into something you can manipulate directly and watch respond.

Deep dive into why GCS is computationally efficient and how it avoids the exponential complexity of traditional solvers. It focuses on Convex Relaxation, Integrality Gap, Strong Formulations, Dual Problems from the “Convex Relaxations and Tightness” section.

The sliders change the key inputs; the “Switch to MIP” button run actions or reset the demo. Every change updates the visualization in real time, so you can see exactly how each variable affects the outcome.

This course explores the Graphs of Convex Sets (GCS) framework, a revolutionary approach to motion planning that unifies discrete graph search with continuous trajectory optimization. It addresses the fundamental challe… This demo is the interactive piece for the “Convex Relaxations and Tightness” section. Open the full Motion Planning with Graphs of Convex Sets course wiki at https://www.getlykke.com/explore/public/motion-planning-with-graphs-of-convex-9ef465dc-e6a7-499a-91ea-ab90b928956f for notes, flashcards, quizzes and the other demos.

You'll build intuition for Convex Relaxation, Integrality Gap, Strong Formulations, Dual Problems — and, crucially, see how they behave when you change the inputs, which is hard to get from a textbook or lecture on Motion Planning with Graphs of Convex Sets alone.