Dynamic pricing in an urban freight environment

Friesz, Terry L.; Mookherjee, Reetabrata; Holguín‐Veras, José; Rigdon, Matthew A.

doi:10.1016/j.trb.2007.08.001

Cited by 27 publications

(9 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Another recent work can be found in Donati et al (2008) wherein the time space in a suitable number of subspaces is discretised with a multi-ant colony system. Regarding urban environment, Friesz et al (2008) discusses a model of dynamic pricing of freight services that follows the paradigm set in the field of revenue management for nonlinear pricing in a dynamic, game theoretic setting. They propose three main entities: sellers, transporters and receivers.…”

Section: Literature Review Of Time-dependent Vrp Modelsmentioning

confidence: 99%

Modelization of Time-Dependent Urban Freight Problems by Using a Multiple Number of Distribution Centers

2009

View full text Add to dashboard Cite

The aim of the paper is to model urban distribution vehicle routing problems by means of hubs in large cities. The idea behind the urban distribution center (DC) is to provide buffer points where cargo and packages which are to be delivered to shops and businesses can be stored beforehand. At these centers, there will be other kinds of routing problems corresponding to other fairly similar distribution problems. In this paper, a new vehicle routing model (based on the known Time-Dependent Vehicle Routing Problem with Time Windows, TDVRPTW) has been carried out and a change in the traditional approach is proposed, by adopting a system in which some customers are served by urban DCs while remaining customers are served by traditional routes. This study is also motivated by recent developments in real time traffic data acquisition systems, as well as national and international policies aimed at reducing concentrations of greenhouse gases emitted by traditional vans. By using k DCs, the whole problem is now composed of k+1 problems: one special VRPTW for each DC in addition to the main problem, in which some customers and k DC are serviced. The model has been tested by simulating one real case of pharmaceutical distribution within the city of Zaragoza.

show abstract

Section: Literature Review Of Time-dependent Vrp Modelsmentioning

confidence: 99%

Modelization of Time-Dependent Urban Freight Problems by Using a Multiple Number of Distribution Centers

2009

View full text Add to dashboard Cite

show abstract

“…Studies commonly propose Gamma, Normal shapes and Poisson function for demand distributions 1,14,9,3 . On the other hand, some of the studies make some assumptions for modeling demand under different price levels based on previous data 14,17,13,9 , some use price elasticity functions derived from previous data 12,11 . In our study, the market is monopolistic and the price has been fixed up to this time.…”

Section: Introductionmentioning

confidence: 99%

A Dynamic Pricing Model for a Maritime Transportation Service Provider

Yanık¹,

Coşgun²,

Ekinci³

2012

IJCIS

View full text Add to dashboard Cite

In this study, the dynamic pricing optimization problem faced by the maritime transportation service provider company is considered. The aim is to find optimal prices for each journey for each level of unsold seats by using probabilistic dynamic programming. Conjoint analysis is used to identify the consumer behavior in case of price changes to the current product, namely journey. The optimal policies show the necessity of applying dynamic pricing policy instead of fixed pricing and the diversification of optimal policies under different conditions.

show abstract

“…Zhang et al (2005) model the interaction between urban freight flows and automobile and data flows using a dynamic game theoretical model and provide an agent based simulation approach to solve the problem. Friesz et al (2008) propose applying a stochastic differential variational inequality model to study the impact of additive demand uncertainty on pricing decisions in an urban freight environment where there three main players: sellers, transporters and receivers. The authors model each players individual objectives using an optimal control problem and use a differential variational inequality and a nonlinear complementarity formulation to represent the combined decision making process.…”

Section: Introductionmentioning

confidence: 99%