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Tight Approximation Algorithms for Scheduling with Fixed Jobs and Nonavailability

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Approximation Algorithms for Allocation and Network Design

Etienne Michel François Bamas

In this thesis, we give new approximation algorithms for some NP-hard problems arising in resource allocation and network design. As a resource allocation problem, we study the Santa Claus problem (also known as the MaxMin Fair Allocation problem) in which ...

EPFL2023

Fair colorful k-center clustering

Ola Nils Anders Svensson, Xinrui Jia

An instance of colorful k-center consists of points in a metric space that are colored red or blue, along with an integer k and a coverage requirement for each color. The goal is to find the smallest radius rho such that there exist balls of radius rho aro ...

SPRINGER HEIDELBERG2021

A (2+epsilon)-Approximation Algorithm for Preemptive Weighted Flow Time on a Single Machine

Lars Rohwedder

Weighted flow time is a fundamental and very well-studied objective function in scheduling. In this paper, we study the setting of a single machine with preemptions. The input consists of a set of jobs, characterized by their processing times, release time ...

ASSOC COMPUTING MACHINERY2021

Learning-Augmented Dynamic Power Management with Multiple States via New Ski Rental Bounds

Adam Teodor Polak, Marek Elias

We study the online problem of minimizing power consumption in systems with multiple power-saving states. During idle periods of unknown lengths, an algorithm has to choose between power-saving states of different energy consumption and wake-up costs. We d ...

2021

Fair Colorful k-Center Clustering

Ola Nils Anders Svensson, Xinrui Jia

An instance of colorful k-center consists of points in a metric space that are colored red or blue, along with an integer k and a coverage requirement for each color. The goal is to find the smallest radius ρ such that there exist balls of radius ρ around ...

Springer2020

Overlapping Multi-Bandit Best Arm Identification

Volkan Cevher, Jonathan Mark Scarlett, Ilija Bogunovic

In the multi-armed bandit literature, the multi-bandit best-arm identification problem consists of determining each best arm in a number of disjoint groups of arms, with as few total arm pulls as possible. In this paper, we introduce a variant of the multi ...

IEEE2019

A Constant-Factor Approximation Algorithm for the Asymmetric Traveling Salesman Problem

Ola Nils Anders Svensson, Jakub Tarnawski

We give a constant-factor approximation algorithm for the asymmetric traveling salesman problem. Our approximation guarantee is analyzed with respect to the standard LP relaxation, and thus our result confirms the conjectured constant integrality gap of th ...

ASSOC COMPUTING MACHINERY2018

Algorithms For Clustering Problems

Ashkan Norouzi Fard

Clustering is a classic topic in combinatorial optimization and plays a central role in many areas, including data science and machine learning. In this thesis, we first focus on the dynamic facility location problem (i.e., the facility location problem in ...

EPFL2018

Dynamic Facility Location via Exponential Clocks

Ola Nils Anders Svensson, Ashkan Norouzi Fard, Hyung Chan An

The dynamic facility location problem is a generalization of the classic facility location problem proposed by Eisenstat, Mathieu, and Schabanel to model the dynamics of evolving social/infrastructure networks. The generalization lies in that the distance ...

Association for Computing Machinery2017

Strengths and Limitations of Linear Programming Relaxations

Abbas Bazzi

Many of the currently best-known approximation algorithms for NP-hard optimization problems are based on Linear Programming (LP) and Semi-definite Programming (SDP) relaxations. Given its power, this class of algorithms seems to contain the most favourable ...

EPFL2017