Dans cet article, nous présentons un modèle des flux de marchandises entre huit régions du Canada, et pour l’ensemble des biens qui ont été regroupés en 64 catégories. Le modèle fonctionne en deux étapes. Dans un premier temps, les flux observés sont régressés sur certaines variables socio-économiques, dont le coût de transport. On obtient alors des flux « a priori », qui peuvent être modifiés lorsque les variables les expliquant sont elles-mêmes modifiées. Or, ces flux « a priori » ne respectent pas nécessairement la structure industrielle de chaque région. Pour les corriger, on résout un programme mathématique dont la fonction objectif est basée sur la théorie de l’information. On cherche alors les flux qui sont les plus proches possibles des flux « a priori », mais qui respectent également la structure industrielle de chaque région. Cette structure est représentée par des contraintes comptables input-output régionales. Le modèle peut être vu comme un modèle input-output interrégional, où les coefficients interrégionaux sont sensibles à des variations des coûts de transport. La formulation du modèle est également beaucoup plus souple et elle permet de prendre en compte d’autres facteurs explicatifs. Le modèle est testé avec des données input-output canadiennes de 1974, et il est aussi comparé à d’autres modèles.

In a previous study, the authors found a positive and significant relationship between computer networks and labor productivity in U.S. manufacturing, using the first survey data on the presence of computer networks in manufacturing plants, collected in the 1999 Computer Network Use Survey. This chapter extends their previous model to include computer capital as a separate input in the production function. It uses new plant-level data on computer investment from the 2000 Annual Survey of Manufactures to develop a proxy for computer capital input. With available data, a sample of new plants is created with the best proxies possible. Based on this sample, positive and significant relationships were found between labor productivity and both computer networks and computer capital inputs. The findings suggest that understanding the relationship between computers and productivity requires measures of how businesses use computers.

Passengers on a transit network with common lines are often faced with the problem of choosing between either to board the arriving bus or to wait for a faster one. Many assignment models are based on the classical assumption that at a given stop passengers board the first arriving carrier of a certain subset of the available lines, often referred to as the attractive set. In this case, it has been shown that, if the headway distributions are exponential, then an optimal subset of lines minimizing the passenger travel time can be easily determined. However, when online information on future arrivals of buses are posted at the stop, it is unlikely that the above classical assumption holds. In this case, passengers may choose to board a line that offers the best combination of displayed waiting time and expected travel time to their destination once boarded. In this paper, we propose a general framework for determining the probability of boarding each line available at a stop when online information on bus waiting times is provided to passengers. We will also show that the classical model without online information may be interpreted as a particular instance of the proposed framework, this way achieving an extension to general headway distributions. The impact of the availability of information regarding bus arrivals and that of the regularity of transit lines on the network loads, as well as on the passenger travel times, will be illustrated with small numerical examples.

In an urban transit system where the service is perceived in terms of frequency of the different lines, the mathematical description of the route choice strategy is not trivial, because the wait at the stop, as pointed out in many studies in the last 30 years, is a complex phenomenon which requires a specific analysis (e.g. Chriqui and Robillard [1975], Marguier [1981], Gendreau [1984], Spiess [1984]). In order to develop an effective model for planning the service, it is very important to define a representation of the wait at transit stops which is at once consistent with users’ behaviour, mathematically sound and practically usable within the more general assignment models. This is the reason that has induced us to rethink globally to the wait problem, by analyzing the stochastic process of vehicle and passenger arrivals at transit stops and the relations among them, without assuming as given facts some hypotheses that are usually adopted. Indeed, some works written during the 80’s [Marguier, 1981; Gendreau, 1984; Marguier and Ceder, 1984] already pointed out that some modelling choices are not easily justifiable, although often utilized in the following years.

In a transit network involving vehicles with rigid capacities, we advocate the use of strategies for describing consumer behavior. At each boarding node, a user sorts the transit lines in decreasing order of preference, and boards the first vehicle in this list whose residual capacity is nonzero. Since a user's position in the queue varies from day to day, the delay experienced is stochastic. This leads to an equilibrium problem where, at a solution. users are assigned to strategies that minimize their expected delay. This situation is formulated as a variational inequality, whose cost mapping is discontinuous and strongly asymmetric, due to the priority of cur-rent passengers over incoming users. We prove that the solution set is nonempty and provide numerical results obtained by an efficient solution algorithm.

This work pleads for the use of the concept of strategies, and their network-theoretic representation as hyperpaths, for modeling network assignment problems. While this concept describes adequately the behavior of users in transit systems, we show that it can apply as well to networks where arc capacities are rigid. This opens up a whole new field of research and raises several questions, from both the theoretical and computational points of view. These are investigated in the paper.

In this paper, we propose a model of dynamic traffic assignment where strategic choices are an integral part of user behaviour. The model is based on a discrete-time description of flow variation through a road network involving arcs with rigid capacities. In such network, a driver's strategy consists in a rule that assigns to each node of the network a set of arcs in the forward star of that node, sorted according to some preference order. The main element of the model is a ‘within-day’ submodel where strategic volumes are loaded onto the network in accordance with the first-in first-out discipline and user preferences. An equilibrium assignment is achieved when expected delays of active strategies are minimal, for every origin-destination pair. We prove the existence of such an assignment and provide numerical results on test networks.

In questo lavoro viene analizzato in dettaglio il fenomeno dell'attesa a una fermata di un servizio di trasporto collettivo urbano, tenendo conto anche della regolarita del passaggio dei veicoli di una stessa linea alla fermata. Viene proposto un modello, detto "dinamico" , che permette di eliminare le contraddizioni insite nel modello usualmente utilizzato. Viene mostrato anche un approccio algoritmico che permette di evitare la propagazione degli errori di approssimazione. Viene anche mostrato un adattamento del modello per quei servizi di trasporto collettivo in cui vi sia informazione all'utenza alle fermate, mediante le "paline intelligenti".

This paper presents a new graph theoretic framework for the passenger assignment problem that encompasses simultaneously the departure time and the route choice. The implicit FIFO access to transit lines is taken into account by the concept of available capacity. This notion of flow priority has not been considered explicitly in previous models. A traffic equilibrium model is described and a computational procedure based on asymmetric boarding penalty functions is suggested.

In this paper, we undertake a detailed study of the bus stop problem in congested transit networks. In the first part of the paper, we present and discuss the bus stop models existing in the literature. In the second part, we propose a new general model for which we prove a number of good properties and we give equivalent formulations. Then, we examine two special cases of the general model. In the first case, the line capacities are considered limited and therefore they can not be exceeded by the on-board passenger flows. In the second case, the strict capacity constraints are relaxed in order to obtain a stop model that can be easily integrated into an assignment model to predict the global passenger behavior in transit networks.

Shortest path problems are among the most studied network flow problems, with interesting applications in various fields. Mainly in large scale transportation systems, a sequence of shortest path problems needs often to be solved, where the (k+1)-th problem differs only slightly from the k-th one. In that context, a promising line of research is to study efficient reoptimization approaches, able to exploit useful information from one shortest path computation to the next one. In this work, we shall focus on the change of the origin node in the shortest path problem to be solved. After reviewing the classical (dual) algorithms described in the literature sofar, which essentially show a Dijkstra''s like behavior, a new dual approach will be proposed, which could be particularly promising in practice.

This paper investigates the application of a logit model to urban transit networks where every set of competitive transit lines is described by a particular graph structure called hyperpath. It shows that a sequential form of the logit model transcends the inherent limitations of the global form while retaining the algorithmic advantages similar to those obtained with the ordinary logit model for private vehicle networks.

In a large variety of applications, equilibrium traffic flows corresponding to a set of slightly modified input data must be computed sequentially. Until now, it is believed that only a disaggregate decomposition approach, that works explicitly on the path flow space, offers the postoptimization capability. This note proposes a new postoptimization method to deal with perturbations of the traffic demand input that does not require path information. Numerical experiments on practical size networks show a drastic reduction in the number of iterations with respect to the naive restart approach.