Learn how to use online, approximation, parallel, randomized, streaming, and machine learning algorithms to optimize your performance and results.

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 ...

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 ...

Learn what an approximation ratio is, how to calculate and compare it for different problems and algorithms, and what are some examples, challenges, and limitations of approximation algorithms and ...

In the current era of technology, multipliers are integral to various hardware accelerators, making the design of efficient multipliers increasingly essential. This research introduces a novel ...

In scheduling theory, the non-preemptive scheduling on a single machine of jobs with increasing processing times and release dates for total completion time minimization is known to be a strongly ...

Approximation and Online Algorithms. (2021). An Improved Approximation Bound for Minimum Weight Dominating Set on Graphs of Bounded Arboricity. Retrieved from http ...

We extend the (1 — 1/e)-approximation algorithm to a constant-factor approximation algorithms for a nonseparable assignment problem with applications in maximizing revenue for budget-constrained ...