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 ...

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 ...

The course will introduce the underlying computational concepts (polynomial-time computation and NP-completeness); introduce canonical problem models including graph problems and formula ...

We consider two generalizations of the fixed job schedule problem, obtained by imposing a bound on the spread-time or on the working time of each processor. These NP-hard problems, studied by the ...

The Stanford researchers apply Grover’s algorithm to the number partitioning problem by encoding each possible partition of the integer list as a quantum state. They also formulate an oracle that can ...

Since cutting stock problems are well known to be NP-hard, it is prohibitive to obtain optimal solutions. We develop approximation algorithms for different purposes: quick response algorithms for ...

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

D-Wave demonstrates performance advantage in quantum simulation The algorithm the researchers use to demonstrate this is known as an interactive proof protocol. Here, one component of the experimental ...

This course is available on the MSc in Applicable Mathematics, MSc in Management Science (Decision Sciences) and MSc in Operations Research & Analytics. This course is available with permission as an ...