Integer Programming

Integer programming (IP) focuses on finding optimal solutions to problems where variables must be integers, a constraint often arising in real-world scenarios. Current research emphasizes applications in diverse fields, including fair resource allocation (e.g., course scheduling, clustering), model interpretability (e.g., rule extraction from machine learning models), and efficient algorithm design (e.g., improved cutting plane methods, novel heuristics using deep learning and genetic algorithms). These advancements are improving the efficiency and applicability of IP across various domains, from logistics optimization to machine learning and beyond, by enabling the solution of increasingly complex problems.