Publications related to Linear programming

Adaptation in Stochastic Algorithms: From Nonsmooth Optimization to Min-Max Problems and Beyond

Stochastic gradient descent (SGD) and randomized coordinate descent (RCD) are two of the workhorses for training modern automated decision systems. Intriguingly, convergence properties of these methods are not well-established as we move away from the spec ...

EPFL2021

On Consensusability of Linear Interconnected Multi-Agent Systems and Simultaneous Stabilization

Giancarlo Ferrari Trecate, Mustafa Sahin Turan, Liang Xu

Consensusability of multi-agent systems (MASs) certifies the existence of a distributed controller capable of driving the states of each subsystem to a consensus value. We study the consensusability of linear interconnected MASs (LIMASs) where, as in sever ...

2021

An Optimal-Storage Approach to Semidefinite Programming Using Approximate Complementarity

Volkan Cevher, Alp Yurtsever

This paper develops a new storage-optimal algorithm that provably solves almost all semidefinite programs (SDPs). This method is particularly effective for weakly constrained SDPs under appropriate regularity conditions. The key idea is to formulate an app ...

SIAM PUBLICATIONS2021

Design of adaptive structures through energy minimization: extension to tensegrity

Gennaro Senatore, Yafeng Wang

This paper gives a new formulation to design adaptive structures through total energy optimization (TEO). This methodology enables the design of truss as well as tensegrity configurations that are equipped with linear actuators to counteract the effect of ...

2021

Computational Inverse Design of Surface-based Inflatables

Mark Pauly, Florin Isvoranu, Tian Chen

We present a computational inverse design method for a new class of surface-based inflatable structure. Our deployable structures are fabricated by fusing together two layers of inextensible sheet material along carefully selected curves. The fusing curves ...

ASSOC COMPUTING MACHINERY2021

Decentralized Proximal Gradient Algorithms With Linear Convergence Rates

Ali H. Sayed, Kun Yuan, Sulaiman A S A E Alghunaim

This article studies a class of nonsmooth decentralized multiagent optimization problems where the agents aim at minimizing a sum of local strongly-convex smooth components plus a common nonsmooth term. We propose a general primal-dual algorithmic framewor ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

A first-order primal-dual method with adaptivity to local smoothness

Volkan Cevher, Maria-Luiza Vladarean

We consider the problem of finding a saddle point for the convex-concave objective

\min_x \max_y f(x) + \langle Ax, y\rangle - g^*(y)

, where

f

is a convex function with locally Lipschitz gradient and

g

is convex and possibly non-smooth. We propose an ...

2021

Coordinating Distributed Energy Resources and Utility-Scale Battery Energy Storage System for Power Flexibility Provision Under Uncertainty

Mohsen Kalantar Neyestanaki

Relying on the power flexibility of distributed energy resources (DERs) located in an active distribution network (ADN), this ADN will be able to provide power flexibility to the upper-layer grid at their point of common coupling (PCC). The power flexibili ...

2021

Innovative Renewable Technology Integration for Nearly Zero-Energy Buildings within the Re-COGNITION Project

Alessandro Francesco Aldo Virtuani

With the 2010/31/EU directive, all new buildings shall be nearly zero-energy buildings (nZEB) from 2020 onward, with the aim of strongly reducing the energy consumption related to the building sector. To achieve this goal, it is not sufficient to focus on ...

MDPI2021

A unifying framework for form-finding and topology-finding of tensegrity structures

Yafeng Wang

This paper presents a unifying framework for the form-finding and topology-finding of tensegrity structures. The novel computational framework is based on rank-constrained linear matrix inequalities. For form-finding, given the topology (i.e., member conne ...

PERGAMON-ELSEVIER SCIENCE LTD2021

Linear programming

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Adaptation in Stochastic Algorithms: From Nonsmooth Optimization to Min-Max Problems and Beyond

On Consensusability of Linear Interconnected Multi-Agent Systems and Simultaneous Stabilization

An Optimal-Storage Approach to Semidefinite Programming Using Approximate Complementarity

Design of adaptive structures through energy minimization: extension to tensegrity

Computational Inverse Design of Surface-based Inflatables

Decentralized Proximal Gradient Algorithms With Linear Convergence Rates

A first-order primal-dual method with adaptivity to local smoothness

Coordinating Distributed Energy Resources and Utility-Scale Battery Energy Storage System for Power Flexibility Provision Under Uncertainty

Innovative Renewable Technology Integration for Nearly Zero-Energy Buildings within the Re-COGNITION Project

A unifying framework for form-finding and topology-finding of tensegrity structures

A first-order primal-dual method with adaptivity to local smoothness

Adaptation in Stochastic Algorithms: From Nonsmooth Optimization to Min-Max Problems and Beyond

Computational Inverse Design of Surface-based Inflatables

Design of adaptive structures through energy minimization: extension to tensegrity

Decentralized Proximal Gradient Algorithms With Linear Convergence Rates

On Consensusability of Linear Interconnected Multi-Agent Systems and Simultaneous Stabilization

An Optimal-Storage Approach to Semidefinite Programming Using Approximate Complementarity

Innovative Renewable Technology Integration for Nearly Zero-Energy Buildings within the Re-COGNITION Project

Coordinating Distributed Energy Resources and Utility-Scale Battery Energy Storage System for Power Flexibility Provision Under Uncertainty

A unifying framework for form-finding and topology-finding of tensegrity structures