Graph cover problems form a critical area within discrete optimisation and theoretical computer science, addressing the challenge of selecting subsets of vertices (or edges) that satisfy predetermined ...

We present a probabilistic greedy search method for combinatorial optimisation problems. This approach is implemented and evaluated for the Set Covering Problem (SCP) and shown to yield a simple, ...

This is an advanced undergraduate course on algorithms. This course examines such topics as greedy algorithms, dynamic programming, graph algorithms, string processing, and algorithms for ...

In life, we sometimes have to make decisions without all the information we want; that’s true in computer science, too. This is the realm of online algorithms — which, despite their name, don’t ...

From greedy shortcuts to dynamic programming guarantees, algorithm design techniques are the backbone of efficient problem-solving in computer science. Understanding when and how to apply each ...

From greedy methods to dynamic programming, mastering algorithm design is about more than theory—it’s about crafting solutions that are efficient, scalable, and practical. Whether you’re preparing for ...

This course studies approximation algorithms – algorithms that are used for solving hard optimization problems. Such algorithms find approximate (slightly suboptimal) solutions to optimization ...