Start working toward program admission and requirements right away. Work you complete in the non-credit experience will transfer to the for-credit experience when you ...

In recent years approximation algorithms based on primal-dual methods have been successfully applied to a broad class of discrete optimization problems. In this paper, we propose a generic primal-dual ...

The travelling salesman problem (TSP) remains one of the most challenging NP‐hard problems in combinatorial optimisation, with significant implications for logistics, network design and route planning ...

Not long ago, a team of researchers from Stanford and McGill universities broke a 35-year record in computer science by an almost imperceptible margin — four hundredths of a trillionth of a trillionth ...

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

The Tactical Fixed Interval Scheduling Problem (TFISP) is the problem of determining the minimum number of parallel nonidentical machines, such that a feasible schedule exists for a given set of jobs.

After 44 years, there’s finally a better way to find approximate solutions to the notoriously difficult traveling salesperson problem. When Nathan Klein started graduate school two years ago, his ...

A team of computer scientists has come up with a dramatically faster algorithm for one of the oldest problems in computer science: maximum flow. The problem asks how much material can flow through a ...