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Exploiting structure of chance constrained programs via submodularity

Related publications (91)

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The Minimization of Public Facilities With Enhanced Genetic Algorithms Using War Elimination

Michael Mark

In this paper, we focus on the problem of minimizing a network of state facilities that provide essential public services (schools, offices, and hospitals). The goal is to reduce the size of the network in order to minimize the costs associated with it. Ho ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2019

Designing Coalition-Proof Reverse Auctions Over Continuous Goods

Maryam Kamgarpour, Orcun Karaca

This paper investigates reverse auctions that involve continuous values of different types of goods, general nonconvex constraints, and second stage costs. We seek to design the payment rules and conditions under which coalitions of participants cannot inf ...

2019

An Inexact Augmented Lagrangian Framework for Nonconvex Optimization with Nonlinear Constraints

Volkan Cevher, Ahmet Alacaoglu, Armin Eftekhari, Fabian Ricardo Latorre Gomez, Mehmet Fatih Sahin

We propose a practical inexact augmented Lagrangian method (iALM) for nonconvex problems with nonlinear constraints. We characterize the total computational complexity of our method subject to a verifiable geometric condition, which is closely related to t ...

2019

New Algorithmic Paradigms for Discrete Problems using Dynamical Systems and Polynomials

Damian Mateusz Straszak

Optimization is a fundamental tool in modern science. Numerous important tasks in biology, economy, physics and computer science can be cast as optimization problems. Consider the example of machine learning: recent advances have shown that even the most s ...

EPFL2018

Distributed Coupled Learning Over Adaptive Networks

Ali H. Sayed, Sulaiman A S A E Alghunaim

This work develops an effective distributed algorithm for the solution of stochastic optimization problems that involve partial coupling among both local constraints and local cost functions. While the collection of networked agents is interested in discov ...

IEEE2018

Traditional joint-space models used to describe equations of motion for humanoid robots offer nice properties linked directly to the way these robots are built. However, from a computational point of view and convergence properties, these models are not th ...

Ieee-Inst Electrical Electronics Engineers Inc2018

Multi-objective optimization tools are becoming increasingly popu-lar in mechanical engineering and allow decision-makers to better understand the inevitable trade-offs. Mechanical design problems can however combine properties that make the use of optimiz ...

2018

A Single-Phase, Proximal Path-Following Framework

Volkan Cevher, Quoc Tran Dinh, Anastasios Kyrillidis

We propose a new proximal path-following framework for a class of constrained convex problems. We consider settings where the nonlinear-and possibly nonsmooth-objective part is endowed with a proximity operator, and the constraint set is equipped with a se ...

INFORMS2018

Distributed Rate Allocation in Switch-Based Multiparty Videoconferencing System

Pascal Frossard, Sergio Mena, Stefano D'Aronco

Multiparty videoconferences, or more generally multiparty video calls, are gaining a lot of popularity as they offer a rich communication experience. These applications have, however, large requirements in terms of both network and computational resources ...

2017

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