We consider a provider of electric vehicle charging that operates a network of charging stations and uses time-varying pricing to maximize profit and reduce ...

The water pump scheduling problem is an optimisation model that determines which water pumps will be turned on or off at each time period over a given time h...

This work introduces a _partitioned optimization framework_ (POf) to ease the solving process for optimization problems for which fixing some variables to a...

This paper addresses the limitations of current satellite payload architectures, which are predominantly hardware-driven and lack the flexibility to adapt to...

This paper tackles a complex variant of the unit commitment (UC) problem at Hydro-Quebec, referred to as the transient stability constrained unit commitmen...

This paper introduces a new step to the Direct Search Method (DSM) to strengthen its convergence analysis. By design, this so-called covering step may e...

We describe the implementation of RipQP, an interior-point algorithm for convex quadratic optimization. Our Julia implementation is open source, and accommo...

This work introduces solar, a collection of ten optimization problem instances for benchmarking blackbox optimization solvers. The instances present differ...

The aim of this paper is to analyze the effect of adaptive investments on international environmental agreements (IEAs) focused on reducing greenhouse gas ...

We propose an approach to construct text-based time-series indices in an optimal way -typically, indices that maximize the contemporaneous relation or the pr...

Integer (linear) programs are a standard way of formalizing a vast array of optimization problems in industry, services, management, science, and technology....

In 1960, Ailsa Land and Alison Doig published the first linear programming-based branch-and-bound algorithm for the solution of mixed integer linear progra...

Heterogeneous datasets emerge in various machine learning or optimization applications that feature different data sources, various data types and complex re...

Randomized algorithms have proven to perform well on a large class of numerical linear algebra problems. Their theoretical analysis is critical to provide gu...

Producing accurate precipitation Intensity-Duration-Frequency (IDF) curves necessitates robust statistical methodologies. Employing a scaling model to combin...

Augmented Lagrangian (AL) methods are a well known class of algorithms for solving constrained optimization problems. They have been extended to the solution...

Millions of oil and gas wells are abandoned and orphaned around the world. Due to funding shortfalls, many abandoned and orphaned wells remain unplugged and ...

Transit authorities are rapidly replacing conventional buses with electric ones because of the increasing concerns about air quality, greenhouse gas emission...

The arithmetic-geometric index is a newly proposed degree-based graph invariant in mathematical chemistry. We give a sharp upper bound on the value of this ...

We reassess Boehmer et al. (2021, BJZZ)'s seminal work on the predictive power of retail order imbalance (ROI) for future stock returns. First, we replicate ...