Concerns about greenhouse gas emissions and government regulations foster the use of electric vehicles. Several recently published articles study the use of electric vehicles (EVs) in node-routing problems. In contrast, this article considers EVs in the context of arc routing while also addressing practically relevant aspects that have not been addressed sufficiently so far. These … Read more
Abstract. We consider the Adaptive Regularization with Cubics approach for solving nonconvex optimization problems and propose a new variant based on inexact Hessian information chosen dynamically. The theoretical analysis of the proposed procedure is given. The key property of ARC framework, constituted by optimal worst-case function/derivative evaluation bounds for first- and second-order critical point, is … Read more
This work describes a new variant of projective splitting for monotone inclusions, in which cocoercive operators can be processed with a single forward step per iteration. This result establishes a symmetry between projective splitting algorithms, the classical forward backward splitting method (FB), and Tseng’s forward-backward-forward method (FBF). Another symmetry is that the new procedure allows … Read more
Intermittent sources of energy represent a challenge for electrical networks, particularly regarding demand satisfaction at peak times. Energy management tools such as load shaving or storage systems can be used to mitigate abrupt variations in the network.The value of different mechanisms to move energy through time is determined by a multi-objective programming approach, that aims … Read more
The Pareto-dominance-basedmulti-objective evolutionary algorithms (MOEAs) have been successful in solving many test problems and other engineering optimization problems. However, their performance gets affected when solving more than 3-objective optimization problems due to lack of sufficient selection pressure. Many attempts have been made by the researchers toward improving the environmental selection of those MOEAs. One such … Read more
Globalized robust optimization has been proposed as a generalization of the standard robust optimization framework in order to allow for a controlled decrease in protection depending on the distance of the realized scenario from the predefined uncertainty set. In this work, we specialize the notion of globalized robustness to Gamma-uncertainty in order to extend its … Read more
This case study deals with a redesign effort to face the overcrowding issue in an Emergency Department (ED). A multidiscinary group of healthcare professionals and engineers worked together to improve the actual processes. We integrate the simulation modeling in a humancentered design method. We use the simulation technique as a learning and experimentation tool into … Read more
In this paper, we introduce an alternative DC algorithm for solving partial DC programs. This proposed algorithm is an natural extension of the standard DC algorithm. Furthermore, we also consider an inexact version of this alternative DC algorithm. The convergence of these proposed algorithms (both the exact and inexact versions) are investigated. The applications to … Read more
In 1988, Barzilai and Borwein published a pioneering paper which opened the way to inexpensively accelerate first-order methods. More in detail, in the framework of unconstrained optimization, Barzilai and Borwein developed two strategies to select the steplength in gradient descent methods with the aim of encoding some second-order information of the problem without computing and/or … Read more
In this paper we study the worst-case complexity of an inexact Augmented Lagrangian method for nonconvex constrained problems. Assuming that the penalty parameters are bounded, we prove a complexity bound of $\mathcal{O}(|\log(\epsilon)|)$ outer iterations for the referred algorithm to generate an $\epsilon$-approximate KKT point, for $\epsilon\in (0,1)$. When the penalty parameters are unbounded, we prove … Read more