We will survey recent work in the design of approximation algorithms for several discrete stochastic optimization problems, with a particular focus on 2-stage problems with recourse. In each of the ...

Geometric optimisation and approximation algorithms form a vibrant research area that intersects computational geometry, combinatorial optimisation and algorithm design. Researchers are dedicated ...

An inner approximation algorithm is proposed for path-constrained dynamic optimization (PCDO) by iteratively solving restrictions of PCDO (RPCDO). Firstly, an upper bound function of the path ...

The Traveling Salesman Problem (TSP) is a well-known problem in optimization, where the objective is to find the shortest route to visit all cities and return to the starting point. This project ...

June 5, 2024 — In a new paper in Science Advances on May 29, researchers at JPMorgan Chase, the U.S. Department of Energy’s (DOE) Argonne National Laboratory and Quantinuum have demonstrated clear ...

Trust Region Preference Approximation: A simple and stable reinforcement learning algorithm for LLM reasoning We propose the Trust Region Preference Approximation (TRPA) algorithm ⚙️, which integrates ...