In practice, the actual approximation factor is far better; we provide a specific example by generating a nearly-optimal inter-league tournament for the 30-team National Basketball Association, with ...

Its second aim is to introduce the averaging principle in the context of two-time-scale stochastic approximation algorithms. We first define the notion of asymptotic efficiency in this framework, then ...

Nash equilibria represent a cornerstone in game theory, defining strategy profiles wherein no player can benefit by unilaterally deviating. This concept underpins a myriad of applications, ranging ...

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

Understand how approximation algorithms compute solutions that are guaranteed to be within some constant factor of the optimal solution. Develop a basic understanding of how linear and integer ...

Such algorithms find approximate (slightly suboptimal) solutions to optimization problems in polynomial time. Unlike heuristics, approximation algorithms have provable performance guarantees: they ...

Although efficient in a strictly theoretical sense (i.e., in the sense of taking polynomial versus exponential time), this algorithm for the permanent is not practical. Indeed, to date, no practical ...