In multi-robot missions, relative position and attitude information between robots is valuable for a variety of tasks such as mapping, planning, and formatio...

Recommender systems provide recommendations to their users for items and services by creating a model tailored to each user to infer their preferences based ...

This paper presents a multiobjective, mixed-integer linear programming (MILP) model that integrates production scheduling, inventory management, and vessel a...

The parameter configuration problem consists of finding a parameter configuration that provides the most effective performance by a given algorithm. This pap...

The most common form of renewable energy production around the world is hydropower. As a result of the growing demand for robust and environmentally friendly...

This note provides a counterexample to a theorem announced in the last part of the paper Analysis of direct searches for discontinuous functions, Mathemati...

Motivated by our collaboration with one of the largest fast-fashion retailers in Europe, we study a two-echelon inventory control problem called the One-Ware...

We consider online optimization problems with time-varying linear equality constraints. In this framework, an agent makes sequential decisions using only pri...

Hydropower producers participate in the electricity market by providing bids in the day-ahead market auctions. Making good bids that obey all market rules an...

This paper studies the properties of a stochastic optimization model for the short-term hydropower generation problem with uncertain inflows. The uncertaint...

In an effort to reduce power system-caused wildfires, utilities carry out public safety power shutoffs (PSPS) in which portions of the grid are de-energized ...

The short-term scheduling of activities in underground mines is an important step in mining operations. This procedure is a challenging optimization problem ...

This paper presents PDENLPModels.jl a new Julia package for modeling and discretizing optimization problems with mixed algebraic and partial differential equ...

In order to improve the efficiency of the last-mile delivery system when customers are possibly absent for deliveries, we propose the idea of employing the c...

Most reinforcement learning methods for adaptive-traffic-signal-control require training from scratch to be applied on any new intersection or after any modi...

In this study, we investigate the best remanufacturing strategy for the original equipment manufacturer (OEM) and independent remanufacturer (IR) in an innov...

We use stochastic dynamic programming to design and solve an extended structural setting for which the illiquidity of the firm's assets under liquidation i...

Providing the right data to a machine learning model is an important step to insure the performance of the model. Non-compliant training data instances may l...

In this paper, we study a novel approach for data-driven decision-making under uncertainty in the presence of contextual information. Specifically, we addres...

This research focuses on the bid optimization problem in the real-time bidding setting for online display advertisements, where an advertiser, or the adverti...