Lecture

Theory of Computation Laboratory 2: Resource Allocation and Network Design

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Description

This lecture covers approximation algorithms for resource allocation problems like the Santa Claus problem and makespan scheduling, as well as for network design problems such as the Traveling Salesman and Steiner forest. It also delves into learning augmented algorithms with predictions, discussing competitive algorithms for the TCP acknowledgment problem and experimental results.

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Related concepts (10)

Approximation algorithm

In computer science and operations research, approximation algorithms are efficient algorithms that find approximate solutions to optimization problems (in particular NP-hard problems) with provable guarantees on the distance of the returned solution to the optimal one. Approximation algorithms naturally arise in the field of theoretical computer science as a consequence of the widely believed P ≠ NP conjecture. Under this conjecture, a wide class of optimization problems cannot be solved exactly in polynomial time.

Competitive analysis (online algorithm)

Competitive analysis is a method invented for analyzing online algorithms, in which the performance of an online algorithm (which must satisfy an unpredictable sequence of requests, completing each request without being able to see the future) is compared to the performance of an optimal offline algorithm that can view the sequence of requests in advance. An algorithm is competitive if its competitive ratio—the ratio between its performance and the offline algorithm's performance—is bounded.

Online algorithm

In computer science, an online algorithm is one that can process its input piece-by-piece in a serial fashion, i.e., in the order that the input is fed to the algorithm, without having the entire input available from the start. In contrast, an offline algorithm is given the whole problem data from the beginning and is required to output an answer which solves the problem at hand. In operations research, the area in which online algorithms are developed is called online optimization.

Polynomial-time approximation scheme

In computer science (particularly algorithmics), a polynomial-time approximation scheme (PTAS) is a type of approximation algorithm for optimization problems (most often, NP-hard optimization problems). A PTAS is an algorithm which takes an instance of an optimization problem and a parameter ε > 0 and produces a solution that is within a factor 1 + ε of being optimal (or 1 – ε for maximization problems). For example, for the Euclidean traveling salesman problem, a PTAS would produce a tour with length at most (1 + ε)L, with L being the length of the shortest tour.

Acknowledgement (data networks)

In data networking, telecommunications, and computer buses, an acknowledgment (ACK) is a signal that is passed between communicating processes, computers, or devices to signify acknowledgment, or receipt of message, as part of a communications protocol. The negative-acknowledgement (NAK or NACK) is a signal that is sent to reject a previously received message or to indicate some kind of error. Acknowledgments and negative acknowledgments inform a sender of the receiver's state so that it can adjust its own state accordingly.

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