Compared to the conventional methods, Artificial Neural Networks (ANN) are considered to be one of the reliable tools for modeling of complex phenomena such as demand. Aim of this study is to provide a model for gasoline demand in transportation section of Tehran metropolis through multilayered perceptron neural network and using the presented model in analyzing the sensitivity of the model to ...

Intelligent Transportation Systems (ITS) have received a great deal of attention in overcoming traffic-associated problems by implementing online traffic management, which inevitably depends on the accurate dynamic traffic demand. Dynamic Traffic Demand is a fundamental input for simulation-based Dynamic Traffic Assignment (DTA) models to describe and predict traffic conditions on the network o...

Facility location-network design (FLND) problem, which determines the location of facilities and also communication links between the demand and facility nodes, is arisen from the combination of the facility location and network design problems. This paper deals with fuzzy capacitated facility location-network design model which aims to select the facilities and candidate links in a way that yi...

This paper considers a dual time scale transportation planning model for which demand evolves on a day-to-day time scale and traffi c flows on arcs of the transportation network fluctuate on a within-day time scale. We show the problem is particularly amenable to a demand learning approach when using a demand model motivated by evolutionary game theory. We then argue that an alternative model o...

The Great East Japan Earthquake that occurred on March 11, 2011 caused disruptions to transportation network such as roads and railways. In general, transportation network disruptions make distribution of relief goods difficult and are considered to have negative impact on the economy of the stricken region owing to a decrease in transportation accessibility. Focusing on Iwate Prefecture, which...

A number of factors influence the efficiency, productivity, and welfare of transportation networks. Travel demand, user costs, and facility supply costs equili-brate on various time scales under a set of pricing (taxes and tolls), investment and ownership policies. Two types of equilibria exist in a transportation network, short-run traffic equilibrium and long-run supply-demand equilibrium. Th...

In this paper, we propose a multi-commodity, discrete kinematic wave model for simulating network traffic flow that possesses the theoretical rigor and computational efficiency inherent in the kinematic wave theory. In this model, 1Author for correspondence (Current address: Institute of Transportation Studies / University of California / 522 Social Science Tower / Irvine, CA 92697-3600 / (949)...

We consider the QoS-aware Multicommodity Flow problem, a natural generalization of the weighted multicommodity flow problem where the demands and commodity values are elastic to the Quality-ofService characteristics of the underlying network. The problem is fundamental in transportation planning and also has important applications beyond the transportation domain. We provide a FPTAS for the QoS...

In this paper we present a methodology to decide capacity expansions for a transit network that finds a robust solution with respect to the uncertainty in demands and travel times. We show that solving for a robust solution is a computationally tractable problem under conditions that are reasonable for a transportation system. For example, the robust problem is tractable for a multicommodity fl...