Sparse Recovery via Partial Regularization: Models, Theory and Algorithms

In the context of sparse recovery, it is known that most of existing regularizers such as $\ell_1$ suffer from some bias incurred by some leading entries (in magnitude) of the associated vector. To neutralize this bias, we propose a class of models with partial regularizers for recovering a sparse solution of a linear system. We … Read more

Acceleration of the PDHGM on strongly convex subspaces

We propose several variants of the primal-dual method due to Chambolle and Pock. Without requiring full strong convexity of the objective functions, our methods are accelerated on subspaces with strong convexity. This yields mixed rates, $O(1/N^2)$ with respect to initialisation and $O(1/N)$ with respect to the dual sequence, and the residual part of the primal … Read more

Blessing of Massive Scale: Spatial Graphical Model Estimation with a Total Cardinality Constraint

We consider the problem of estimating high dimensional spatial graphical models with a total cardinality constraint (i.e., the l0-constraint). Though this problem is highly nonconvex, we show that its primal-dual gap diminishes linearly with the dimensionality and provide a convex geometry justification of this ‘blessing of massive scale’ phenomenon. Motivated by this result, we propose … Read more

Partial outer convexification for traffic light optimization in road networks

We consider the problem of computing optimal traffic light programs for urban road intersections using traffic flow conservation laws on networks. Based on a Partial Outer Convexification approach, which has been successfully applied in the area of mixed-integer optimal control for systems of ordinary or differential algebraic equations, we develop a computationally tractable two-stage solution … Read more

A Benders Decomposition Approach for the Charging Station Location Problem with Plug-in Hybrid Electric Vehicles

The flow refueling location problem (FRLP) locates $p$ stations in order to maximize the flow volume that can be accommodated in a road network respecting the range limitations of the vehicles. This paper introduces the charging station location problem with plug-in hybrid electric vehicles (CSLP-PHEV) as a generalization of the FRLP. We consider not only … Read more

An Extended Frank-Wolfe Method with “In-Face” Directions, and its Application to Low-Rank Matrix Completion

We present an extension of the Frank-Wolfe method that is designed to induce near-optimal solutions on low-dimensional faces of the feasible region. We present computational guarantees for the method that trade off efficiency in computing near-optimal solutions with upper bounds on the dimension of minimal faces of iterates. We apply our method to the low-rank … Read more

Free-Floating Bike Sharing: Solving Real-life Large-scale Static Rebalancing Problems

Free-floating bike sharing (FFBS) is an innovative bike sharing model. FFBS saves on start-up cost, in comparison to station-based bike sharing (SBBS), by avoiding construction of expensive docking stations and kiosk machines. FFBS prevents bike theft and offers significant opportunities for smart management by tracking bikes in real-time with built-in GPS. However, like SBBS, the … Read more

Modulation Design for Two-Way Amplify-and-Forward Relay HARQ

As a practical technique for enhancing relay and HARQ transmissions, Modulation Diversity (MoDiv) uses distinct constellation mappings for data retransmissions. In this work, we study the MoDiv optimization in a amplify-and-forward (AF) two-way relay channel (TWRC). The design of MoDiv design to minimize the bit-error rate (BER) is formulated into a successive Koopmans-Beckmann Quadratic Assignment … Read more

New Exact Approaches to Row Layout Problems

Given a set of departments, a number of rows and pairwise connectivities between these departments, the multi-row facility layout problem (MRFLP) looks for a non-overlapping arrangement of these departments in the rows such that the weighted sum of the center-to-center distances is minimized. As even small instances of the (MRFLP) are rather challenging, several special … Read more

A robust optimization model for the risk averse reservoir management problem

This paper presents a new formulation for the risk averse stochastic reservoir management problem. Using recent advances in robust optimization and stochastic programming, we propose a dynamic, multi-objective model based on minimization of a multidimensional risk measure associated with floods and droughts for a hydro-electrical complex. We present our model and then identify approximate solutions … Read more