This study investigates the feasibility of large-scale distributed networks. The core focus of our research is the impact of multi-hop communication on point...

Planners in different industries use optimization software for decision-making. In numerous practical applications, these optimization tools are often not re...

In the multi-commodity two-echelon vehicle routing problem with time windows (MC-2E-VRPTW), first-echelon vehicles transport goods from depots to satellites...

Hydrogen is emerging as a crucial energy source in the global effort to reduce dependence on fossil fuels and meet climate goals. Integrating hydrogen into I...

This study explores accelerating strategies in column generation (CG) to effectively solve online dial-a-ride problems in large-scale ride-sharing systems. ...

Managing intermittent generation in electric power systems with high penetration of renewable sources of energy presents major operational challenges. Faster...

The routing-and-driving problem for plug-in hybrid electric vehicles (PHEVs) is an extension of the vehicle routing problem with time windows, where routing ...

This paper addresses the Integrated Electrical Drill Rig Dispatching and Drilling Coordination Problem (IDRDCP) in open-pit mining operations, combining mach...

This paper addresses the difficulties mining companies face in planning their digital transformation. Based on the literature on project portfolio manageme...

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

Linear quadratic games on very large dense networks are modelled with discrete time linear quadratic graphon field games with Q-noise. In such a game, the ag...

For sequences of networks embedded in the unit cube \([0, 1]^m\), (weak) measure limits of sequences of empirical measures of vertex densities (vertexon...

This paper addresses the scheduling of electrical drilling machines in open-pit mines, proposing three constraint programming formulations to account for unc...

This paper presents a partial outsourcing strategy for the vehicle routing problem with stochastic demands (VRPSD), and routing reoptimization is considered ...

JSOSuite.jl is a new Julia package offering a user-friendly interface for continuous nonlinear optimization. The solvers available cover unconstrained to g...

Major projects often deviate from their expected budget, schedule, and benefits. Existing techniques to improve the forecasted outcome, such as the Refer...

Elastic Optical Networks (EONs) are challenged by spectrum fragmentation, which can obstruct the establishment of new connections. While the concept of fragm...

The modelling of linear quadratic Gaussian optimal control problems on large complex networks is intractable computationally. Graphon theory provides an appr...

This article addresses the efficient coordination of multiple electrical drill rigs in open-pit mines, considering unique constraints such as continuous powe...

This paper introduces new model parameterizations for learning dynamical systems from data via the Koopman operator, and studies their properties. Whereas mo...

As climate change intensifies, the shift to cleaner energy sources becomes increasingly urgent. With wind energy production set to accelerate, reliable win...

Designing efficient evacuation networks is crucial for disaster preparedness, as poorly planned and managed evacuations can increase the time required for ev...

When performing a Systematic Literature Review (SLR), the Abstract Screening Process (ASP) can be a very consuming and laborious task, especially when rese...

The Quadratic Knapsack Problem (QKP) is a challenging combinatorial optimization problem that has attracted significant attention due to its complexity and p...

Population growth and city sprawl have been driving increasing amounts of traffic congestion in multiple major cities worldwide. In this scenario, developing...

In this report, we present our winning solution to the 16th AIMMS-MOPTA Optimization Modeling Competition on whether a fully renewable energy grid would bene...

The solution of the graphon mean field game equation (GMFG) is characterized by an HJB equation and an FPK equation coupled via a graphon mean field. An a...

We develop R2N, a modified quasi-Newton method for minimizing the sum of a \(\mathcal{C}^1\) function \(f\) and a lower semi-continuous prox-bounded `(h...

Penalty methods are a well known class of algorithms for constrained optimization. They transform a constrained problem into a sequence of unconstrained _pe...

We explore a scaled spectral preconditioner for the efficient solution of sequences of symmetric and positive-definite linear systems. We design the scaled...

We extend traditional complexity analyses of trust-region methods for unconstrained, possibly nonconvex, optimization. Whereas most complexity analyses as...

Governments are motivated to subsidize profit-driven firms that manufacture zero-emission vehicles to ensure they become price-competitive. This paper intr...

We consider mean field social optimization in nonlinear diffusion models. By dynamic programming with a representative agent employing cooperative optimize...

Local search methods start from a feasible solution and improve it by successive minor modifications until a solution that cannot be further improved is enco...

The increasing penetration of renewable electricity generation as well as the implementation of demand response programs has led to new challenges in the ope...

Over the past years, Robotic Process Automation (RPA) has emerged as a significant tool to enhance productivity across various industries by automating repet...

The cubic knapsack problem (CKP) is a combinatorial optimization problem, which can be seen both as a generalization of the quadratic knapsack problem (QKP) ...

Bistable mechanical systems exhibit two stable configurations where the elastic energy is locally minimized. To realize such systems, origami techniques ha...

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

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

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...

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 ...

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

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

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

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

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...

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

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

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

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 ...

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

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 ...

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

The truck loading and inventory routing problems are the two most important decisions made by companies replenishing petrol stations. This paper investigates...

This poster conceptually lays out recent advances in trustworthy machine learning (ML) that are of great interest for power systems applications like virtu...

Efficiently solving a vehicle routing problem (\(\mathcal{VRP}\)) in a practical runtime is a critical challenge for delivery management companies. This pa...

This paper describes a planning problem faced by a fast-growing petroleum company in West Africa. The problem is a complex variant of the petrol station repl...

Cellular solids are structures which have applications in mechanical engineering to make lightweight structures and heat exchangers, in biomedical engineer...

Vehicle routing problems (VRPs) with deadlines have received significant attention around the world. Motivated by a real-world food delivery problem, we assu...

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 ...

We develop a trust-region method for minimizing the sum of a smooth term \(f\) and a nonsmooth term \(h\), both of which can be nonconvex. Each iteratio...

The Thirteenth Montreal IPSW took place on August 21-25, 2023, and was jointly organized by the Centre de recherches mathématiques (CRM) and the Institute ...

The purpose of the present note is to bring clarifications to certain concepts and surrounding notation of Aravkin et al. (2022). All results therein contin...

We develop a worst-case evaluation complexity bound for trust-region methods in the presence of unbounded Hessian approximations. We use the algorithm of Ar...

We develop an interior-point method for nonsmooth regularized bound-constrained optimization problems. Our method consists of iteratively solving a sequence...

The fine-tuning of Large Language Models (LLMs) has enabled them to recently achieve milestones in natural language processing applications. The emergenc...

In this work, we study a class of two-player deterministic finite-horizon difference games with coupled inequality constraints, where both players have two t...

Le problème du partitionnement d'ensemble est un problème de programmation en nombres entiers très étudié. Le problème consiste à trouver une partition de tâ...

Yield uncertainty is an important issue in various industries such as agriculture, food, and textile where the production output is reliant on uncontrollable...

Bus scheduling in public transit consists in determining a set of bus schedules to cover a set of timetabled trips at minimum cost. This planning process has...

We extend the \(\alpha\) and \(\beta\) characteristic functions (CFs) to cooperative interval games, which constitute an interesting class of games t...

The Harwell Subroutine Library (HSL) is a renowned suite of efficient and robust numerical algorithms designed to tackle complex mathematical problems such a...

In this work, we propose a non-intrusive and training free method to detect behind-the-meter (BTM) electric vehicle (EV) charging events from the data measur...

Determining optimal inventory replenishment decisions requires balancing the costs of excess inventory with shortage risks. While demand uncertainty has been...

In this work, we improve the efficiency of Unit Commitment (UC) optimization solvers using a Graph Convolutional Neural Network (GCNN). In power systems, UC ...

A challenge in aircraft design optimization is the presence of non-computable, so-called hidden, constraints that do not return a value in certain regions of...

This paper introduces the Heterogeneous-Fleet Electric Vehicle Routing Problem with Nonlinear Charging Functions (HEVRP-NL). This problem involves routing a ...

Inventory management for slow-moving items is challenging due to their high intermittence and lumpiness. Recent developments in machine learning and computat...

The cosine measure was introduced in 2003 to quantify the richness of a finite positive spanning sets of directions in the context of derivative-free direc...