The dynamic parking allocation problem : theoretical and practical solution methods

Cette thèse s’intéresse à la problématique du stationnement en milieu urbain, en particulier en période de forte affluence. Un des objectifs principaux est l’exploration de méthodes issues de la recherche opérationnelle pour apporter des solutions pratiques via la programmation mathématique et les heuristiques. Nous considérons dans un premier temps une version simplifiée, statique du problème, dans laquelle l’ensemble des données nécessaires est fixé et déterministe sur un horizon d’une journée. Un modèle en variables 0-1, dérivé du problème d’affectation généralisée est proposé et testé sur un ensemble d’instances généré aléatoirement. Des extensions qui incluent des fonctions objectives différentes et d’autres modes de transport sont aussi examinées. De plus, nous avons proposé une heuristique basée sur la recherche à voisinage variable pour obtenir rapidement une solution de qualité satisfaisante. La nature dynamique du problème nous a conduit à adapter ce modèle de façon à pouvoir prendre en compte les mises à jour continues des données. Nous avons ainsi proposé et évalué plusieurs politiques et scénarios, avec l’ambition d’obtenir un système qui soit le plus adaptatif et robuste possible. Le système proposé doit pouvoir guider les utilisateurs vers une place qui leur est affectée lorsque cela est possible, ou à défaut vers leur destination. Notre approche est validée via un ensemble de simulations réalisées à partir de données réelles collectées depuis trois grandes villes européennes.This thesis focuses on the problem of urban parking, especially in peak traffic hours. One of the main objectives is to explore the solution methods from operational research perspective and to provide practical solutions throug h mathematical programming and heuristics. We first consider a simplified, static version of the problem in which all the necessary data is fixed and deterministic over a one-day planning horizon. A 01 programming model derived from the generalized assignment problem is proposed and tested on a randomly generated set of instances. Extensions that include different objective functions and other modes of transport are also examined. In addition, we proposed a heuristic based on variable neighborhood search to quickly obtain a good quality solutions. The dynamic nature of the problem has led us to adapt this model so that it can take into account the continuous data updates. We have proposed and evaluated several policies and scenarios, with the goal of developing a system that is as adaptive and robust as possible. The proposed system should be able to guide users to a parking lot assigned to them when possible, or to their destination when their is no parking slot available. Our approach is corroborated via simulation over a set of real data collected from three major European cities

Le problème d'affectation de places de stationnement dynamique: Solutions pratiques et théoriques

This thesis focuses on the problem of urban parking, especially in peak traffic hours. One of the main objectives is to explore the solution methods from operational research perspective and to provide practical solutions through mathematical programming and heuristics.We first consider a simplified, static version of the problem in which all the necessary data is fixed and deterministic over a one-day planning horizon. A 0-1 programming model derived from the generalized assignment problem is proposed and tested on a randomly generated set of instances. Extensions that include different objective functions and other modes of transport are also examined. In addition, we proposed a heuristic based on variable neighborhood search to quickly obtain a good quality solutions.The dynamic nature of the problem has led us to adapt this model so that it can take into account the continuous data updates. We have proposed and evaluated several policies and scenarios, with the goal of developing a system that is as adaptive and robust as possible. The proposed system should be able to guide users to a parking lot assigned to them when possible, or to their destination when their is no parking slot available.Our approach is corroborated via simulation over a set of real data collected from three major European cities.Cette thèse s'intéresse à la problématique du stationnement en milieu urbain, en particulier en période de forte influence. Un des objectifs principaux est l'exploration de méthodes issues de la recherche opérationnelle pour apporter des solutions pratiques via la programmation mathématique et les heuristiques.Nous considérons dans un premier temps une version simplifiée, statique du problème, dans laquelle l'ensemble des données nécessaires est fixé et déterministe sur un horizon d'une journée. Un modèle en variables 0-1, dérivé du problème d'affectation généralisée est proposé et testé sur un ensemble d'instances généré aléatoirement. Des extensions qui incluent des fonctions objectives différentes et d'autres modes de transport sont aussi examinés. De plus, nous avons proposé une heuristique basée sur la recherche à voisinage variable pour obtenir rapidement une solution de qualité satisfaisante.La nature dynamique du problème nous a conduit à adapter ce modèle de façon à pouvoir prendre en compte les mise à jour continues des données. Nous avons ainsi proposé et évalué plusieurs politiques et scénarios, avec l'ambition d'obtenir un système qui soit le plus adaptatif et robuste possible. Le système proposé doit pouvoir guider les utilisateurs vers une place qui leur est affectée lorsque cela est possible, ou à défaut vers leur destination.Notre approche est validée via un ensemble de simulations réalisées à partir de données réelles collectées depuis trois grandes villes européennes

Effects of thermal disorder on the electronic structure of halide perovskites: insights from MD simulations

The effects of thermal disorder on the electronic properties of organic/inorganic halide perovskites were investigated using ab initio molecular dynamics simulations. It was generally found that band gap variations due to effects of thermal disorder are the largest in materials with the smallest lattice constant. The factors that may lead to departure from this trend include the degree of rotational and translational motion of the organic cation and the strength of its dipole. It was found that the contribution of the flexible organic part to the band gap variations is considerably smaller than the contribution of the inorganic part of the material. The results of our simulations indicate that band gap variations in halide perovskites fall within the range exhibited in inorganic semiconductors

Adaptive general variable neighborhood search heuristics for solving the unit commitment problem

International audienceThe unit commitment problem (UCP) for thermal units consists of finding an optimal electricity production plan for a given time horizon. In this paper we propose hybrid approaches which combine Variable Neighborhood Search (VNS) metaheuristic and mathematical programming to solve this NP-hard problem. Four new VNS based methods, including one with adaptive choice of neighborhood order used within deterministic exploration of neighborhoods, are proposed. A convex economic dispatch subproblem is solved by Lambda iteration method in each time period. Extensive computational experiments are performed on well-known test instances from the literature as well as on new large instances generated by us. It appears that the proposed heuristics successfully solve both small and large scale problems. Moreover, they outperform other well-known heuristics that can be considered as the state-of-the-art approaches

Variable Neighbourhood Decent for Parking Allocation Problem

National audienceSearching for available parking lots presents a mayor problem in urban areas.Massive unorganized pursuit for parking provokes traffic congestion, financial losses, negativeenvironmental effects, among others. Most studies on this topic base their research on simulations due to the large set of non-deterministic input. In this paper we propose an approachwhere each vehicle that is looking for a parking lot is equipped with GPS device. Based on thisassumption, the static Parking allocation problem (PAP) can be modeled as a variant of Generalized assignment problem (GAP). Here we also discuss inclusion of the static model into adynamic real-world circumstances. Moreover, we developed a heuristic based on sequential Variable Neighborhood Decent (VND) to solve static PAP. It uses two neighborhood structures :reallocation and interchange. It appears that the deviation of VND based heuristic, comparedwith the optimal solutions, are always less than 0.1%

Variable Neighbourhood Decent for Parking Allocation Problem

National audienceSearching for available parking lots presents a mayor problem in urban areas.Massive unorganized pursuit for parking provokes traffic congestion, financial losses, negativeenvironmental effects, among others. Most studies on this topic base their research on simulations due to the large set of non-deterministic input. In this paper we propose an approachwhere each vehicle that is looking for a parking lot is equipped with GPS device. Based on thisassumption, the static Parking allocation problem (PAP) can be modeled as a variant of Generalized assignment problem (GAP). Here we also discuss inclusion of the static model into adynamic real-world circumstances. Moreover, we developed a heuristic based on sequential Variable Neighborhood Decent (VND) to solve static PAP. It uses two neighborhood structures :reallocation and interchange. It appears that the deviation of VND based heuristic, comparedwith the optimal solutions, are always less than 0.1%

The application of the artificial neural network in analysing the spread quality

In this paper, we introduce a new approach in food processing using an artificial intelligence. The main focus is simulation of production of spreads and chocolate as representative confectionery products. This approach aids to speed up, model, optimize, and predict the parameters of food processing trying to increase quality of final products. An artificial intelligence is used in field of neural networks and methods of decisions

Why choosing the right partner is important: stabilization of ternary Cs(y)GUA(x)FA((1-y-x))PbI(3)perovskites

Lead halide perovskites with mixtures of monovalent cations have attracted wide attention due to the possibility of preferentially stabilizing the perovskite phase with respect to photovoltaically less suitable competing phases. Here, we present a theoretical analysis and interpretation of the phase stability of binary (CH6N3)(x)[HC(NH2)(2)]((1-x))PbI3= GUA(x)FA((1-x))PbI(3)and ternary Cs(y)GUA(x)FA((1-y-x))PbI(3)mixtures. We first estimate if such mixtures are stable and if they lead to a stabilization of the perovskite phase based on static Density Functional Theory (DFT) calculations. In order to investigate the finite temperature stability of the phases, we also employ first-principles molecular dynamics (MD) simulations. It turns out that in contrast to the FA(+)-rich case of FA/Cs mixtures, although mixing of FA/GUA is possible, it is not sufficient to stabilize the perovskite phase at room temperature. In contrast, stable ternary mixtures that contain 17% of Cs(+)can be formed that lead to a preferential stabilization of the perovskite phase. In such a way, the enthalpic destabilization due to the introduction of a too large/too small cation that lies outside the Goldschmidt tolerance range can be (partially) compensated through the introduction of a third cation with complementary size. This allows to suggest a new design principle for the preparation of stable perovskite structures at room temperature with cations that lie outside the Goldschmidt range through mixtures with size-complementary cations in such a way that the effective average cation radius of the mixture lies within the stability range