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 ...

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

The algorithm we propose, IES, gives an approximate solution to the LHD problem regardless of its dimension and size with a theoretical performance guarantee. We introduce two upper bounds for the ...

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 ...

This paper proposes an algorithm that automatically translates the "continuum approximation" (CA) recipes for location problems into discrete designs. It applies to terminal systems, but can also be ...