Variable fixing by reduced costs is a popular technique for accelerating the solution process of mixed-integer linear programs. For vehicle routing problems ...

User-centered logistics aiming at customer satisfaction are gaining importance due to growing e-commerce and home deliveries. Customer satisfaction can be ...

In this paper, we introduce a class of deterministic finite-horizon two-player non-zero-sum differential games where one player uses continuous control wh...

Significant progress has been made in the field of computer vision, due to the development of supervised machine learning algorithms, which efficiently extra...

Since nonprofit organizations play an important role in providing goods and services in all countries, this paper aims at determining optimal policies for ...

We analyze an endogenous growth model with non-constant discounting and a negative externality of growth on utility. With a decreasing rate of impatience, ...

This paper studies the Dynamic Facility Location Problem with Modular Capacities (DFLPM). We propose a linear relaxation based heuristic (LRH) and an evoluti...

We build upon Estrin et al. (2019) to develop a general constrained nonlinear optimization algorithm based on a smooth penalty function proposed by Fletch...

In large commercial airlines, the monthly schedule (roster) of the crew members is usually determined by solving two problems sequentially, namely, the crew ...

We present a case study of using machine learning classification algorithms to initialize a large scale commercial operations research solver (GENCOL) in the...

The minimum residual method (MINRES) of Paige and Saunders (1975), which is often the method of choice for symmetric linear systems, is a generalization of t...

Given $n$ points, a symmetric dissimilarity matrix $D$ of dimensions $n\times n$ and an integer $p\geq 2$, the $p$-dispersion problem (pD...

We study the time evolution of a vertically and horizontally differentiated oligopolistic industry, where firms compete in quantity and are divided into gr...

In the Inventory Routing Problem customer demand is satisfied from inventory which is replenished with capacitated vehicles. The objective is to minimize tot...

Multi-agent reinforcement learning has made significant progress in recent years, but it remains a hard problem. Hence, one often resorts to developing lea...

We propose an iterative method named USYMLQR for the solution of symmetric saddle-point systems that exploits the orthogonal tridiagonalization method of Sa...

We propose a regularization method for nonlinear least-squares problems with equality constraints. Our approach is modeled after those of Arreckx and Orban ...

We are interested in blackbox optimization for which the user is aware of monotonic behaviour of some constraints defining the problem. That is, when incr...

We are witnessing an acceleration in the uptake of renewable energy in power systems. Because of the associated variability and uncertainty of renewables, ...

Recommender systems make use of different sources of information for providing users with recommendations of items. Such systems are often based on collabor...