Network Synthesis

Contains research objectives and reports on two research projects

Scheduling Maintenance in Wind Farms

International audienc

Local Elected Officials’ Receptivity to Refugee Resettlement in the United States

Local leaders possess significant and growing authority over refugee resettlement, yet we know little about their attitudes toward refugees. In this article, we use a conjoint experiment to evaluate how the attributes of hypothetical refugee groups influence local policymaker receptivity toward refugee resettlement. We sample from a novel, national panel of current local elected officials, who represent a broad range of urban and rural communities across the United States. We find that many local officials favor refugee resettlement regardless of refugee attributes. However, officials are most receptive to refugees whom they perceive as a strong economic and social fit within their communities. Our study is the first in a growing literature on individual attitudes toward refugees to systematically examine the preferences of US local elected officials and offers unique insights into the views of this influential and policy-relevant group

A Benders-based branch-and-cut approach to solve a wind turbine maintenance scheduling problem

We deal with a maintenance scheduling problem rising in the onshore wind power industry. We address the problem on a short-term horizon considering an individual management of the technicians through a space-time tracking. The objective is to find a maintenance planning that maximizes the production of the turbines while taking into account wind predictions, multiple task execution modes, and task-technician assignment constraints. We introduce an exact method to solve this challenging problem. We first propose integer linear programming (ILP) formulations of this problem. Then, on this basis, we build up a Benders-based branch-and-cut approach making use of Benders cuts as well as problem-specific cuts. Our method solves to optimality most of the instances or delivers solutions with a small average gap with respect to upper bounds. The results suggest that our method significantly outperforms the direct resolution of ILP models

A branch-and-check approach to solve a short-term maintenance scheduling problem faced by the onshore wind industry

International audienc

Maintenance scheduling in the electricity industry: A literature review

The reliability of the power plants and transmission lines in the electricity industry is crucial for meeting demand. Consequently, timely maintenance plays a major role reducing breakdowns and avoiding expensive production shutdowns. By now, the literature contains a sound body of work focused on improving decision making in generating units and transmission lines maintenance scheduling. The purpose of this paper is to review that literature. We update previous surveys and provide a more global view of the problem: we study both regulated and deregulated power systems and explore some important features such as network considerations, fuel management, and data uncertainty

A MIP Model and Several Approaches to Schedule Maintenance in Wind Farms on a Short-term Horizon

Taking into account wind prediction when scheduling maintenance on wind turbines can lead to potential gains. Preemption, transfer times for resources, and outsourcing are considered in this problem. The objective is concerned with maximizing the difference between the profits of wind farms related to the estimated production and the costs associated with outsourcing and resources transfers. A MIP model, a benders decomposition technique and a constraint programming approach are proposed

Planification du service des agents de conduite de trains commerciaux de passagers

Notre étude porte sur la planification des emplois du temps des Agents de Conduite (AdC) de trains de passagers. Dans le ferroviaire, ce problème de "crew scheduling" est souvent résolu en trois étapes successives : 1) génération de Journées de Service (JS) (plannings réglementaires d\u27un AdC sur une journée), 2) mise en place de tournées (enchaînement de deux JS, avec découché éventuel) et 3) mise en place de grilles horaires (plannings hebdomadaires respectant des contraintes de capacité d\u27effectifs).  Nous traitons ici un problème qui intègre les étapes 1 et 2, et porte des contraintes a priori de capacité d\u27effectifs. Le principal objectif consiste à couvrir le maximum de trains, mais d\u27autres critères tels que le nombre de découchés sont aussi optimisés.  Nous proposons une approche de type " Generate-And-Select " dans laquelle on génère dans un premier temps des emplois du temps (JS et tournées) réalisables du point de vue des contraintes, puis on en sélectionne un sous-ensemble répondant au mieux aux objectifs. La phase de génération est une énumération contrôlée par un moteur interne de règles. La phase de sélection est une heuristique lagrangienne combinée à des techniques de fixation de colonnes et de " pricing ", adaptée de Caprara et al. Elle est basée sur un algorithme en 3 phases : algorithme de sous-gradient, heuristique et phase de fixations d\u27emplois du temps dans la solution.  Des expérimentations ont été menées sur des données réelles issues de la production TER d\u27une région française sur une semaine-type. Nous obtenons des solutions de qualité (en comparaison d\u27un solveur commercial), cohérentes avec le métier et ne nécessitant pas le recours à un solveur externe de programmation mathématique