An ADMM-Based Interior-Point Method for Large-Scale Linear Programming

In this paper, we propose a new framework to implement interior point method (IPM) in order to solve some very large scale linear programs (LP). Traditional IPMs typically use Newton’s method to approximately solve a subproblem that aims to minimize a log-barrier penalty function at each iteration. Due its connection to Newton’s method, IPM is … Read more

Sensitivity Analysis for Nonlinear Programming in CasADi

We present an extension of the CasADi numerical optimization framework that allows arbitrary order NLP sensitivities to be calculated automatically and efficiently. The approach, which can be used together with any NLP solver available in CasADi, is based on a sparse QR factorization and an implementation of a primal-dual active set method. The whole toolchain … Read more

Solving Time Dependent Traveling Salesman Problems with Time Windows

We present a new solution approach for the Time Dependent Traveling Salesman Prob- lem with Time Windows. This problem considers a salesman who departs from his home, has to visit a number of cities within a pre-determined period of time, and then returns home. The problem allows for travel times that can depend on the … Read more

Inexact Stochastic Mirror Descent for two-stage nonlinear stochastic programs

We introduce an inexact variant of Stochastic Mirror Descent (SMD), called Inexact Stochastic Mirror Descent (ISMD), to solve nonlinear two-stage stochastic programs where the second stage problem has linear and nonlinear coupling constraints and a nonlinear objective function which depends on both first and second stage decisions. Given a candidate first stage solution and a … Read more

A Fully Distributed Dual Consensus ADMM Based on Partition for DC-OPF with Carbon Emission Trading

This paper presents a novel fully distributed alternating direction method of multipliers (ADMM) approach for solving the direct current optimal power flow with carbon emission trading (DC-OPF-CET) problem. Different from the other ADMM-based distributed approaches which disclosing boundary buses and branches information among adjacent subsystems, our proposed method adopts a new strategy by using ADMM … Read more

A proximal minimization algorithm for structured nonconvex and nonsmooth problems

We propose a proximal algorithm for minimizing objective functions consisting of three summands: the composition of a nonsmooth function with a linear operator, another nonsmooth function, each of the nonsmooth summands depending on an independent block variable, and a smooth function which couples the two block variables. The algorithm is a full splitting method, which … Read more

Stochastic subgradient method converges on tame functions

This work considers the question: what convergence guarantees does the stochastic subgradient method have in the absence of smoothness and convexity? We prove that the stochastic subgradient method, on any semialgebraic locally Lipschitz function, produces limit points that are all first-order stationary. More generally, our result applies to any function with a Whitney stratifiable graph. … Read more

The optimal design of low-latency virtual backbones

Two nodes of a wireless network may not be able to communicate with each other directly perhaps due to obstacles or insufficient signal strength. This necessitates the use of intermediate nodes to relay information. Often, one designates a (preferably small) subset of them to relay these messages (i.e., to serve as a virtual backbone for … Read more

Piecewise constant decision rules via branch-and-bound based scenario detection for integer adjustable robust optimization

Multi-stage problems with uncertain parameters and integer decisions variables are among the most difficult applications of robust optimization (RO). The challenge in these problems is to find optimal here-and-now decisions, taking into account that the wait-and-see decisions have to adapt to the revealed values of the uncertain parameters. Postek and den Hertog (2016) and Bertsimas … Read more