An Environmental Approach to Optimize Urban Freight Transport Systems
Abstract
This chapter proposes an optimization-simulation model for planning and managing an urban freight transport system, which has to serve one or more points of the network that receive and/or generate a great volume of cargo, using trucks. This type of transport has special characteristics and generates significant impacts: increased traffic congestion, due to the presence of large vehicles which take up much space and are very slow; and air pollution caused by the extra traffic volume and the extra congestion. Therefore, the purpose of the model is to minimize these negative effects on the environment and on the users of the local road network. To achieve this goal, the authors propose and solve an optimization problem to minimize the total system cost (operating costs of the suppliers, costs supported by private vehicle users and public transport users, operating costs of the public transport, etc.). The proposed optimization problem is a bi-level mathematical programming model, where the upper level defines the total cost of the system, and the lower level defines the behaviour of private and public users, assuming that each of them chooses the route that minimizes his total journey cost. Then, this model is applied to the real case in the city of Santander (Northern Spain) obtaining a series of interesting conclusions from the corresponding sensitivity analysis.
Keywords
Urban freight Optimization EnvironmentReferences
- 1.Reiner, G., Traka, T.: Customized supply chain design: problems and alternatives for a production company in the food industry. Int. J. Prod. Econ. 89(2), 217–229 (2004)CrossRefGoogle Scholar
- 2.Siprelle, A.J., Parsons, D.J., Clark, R.J.: Benefits of using a supply chain simulation tool to study inventory allocation. In: Proceedings of the 2003 Winter Simulation Conference (2003)Google Scholar
- 3.Boerkamps, J., Binsbergen, A.V.: GoodTrip a new approach for modelling and evaluation of urban goods distribution. In: Proceedings 1st International Conference on City Logistics: City Logistics, Australia (1999)Google Scholar
- 4.Shinghal, N., Fowkes, T.: Freight mode choice and adaptive stated preferences. Transp. Res. Part E Logist. Transp. Rev. 38(5), 367–378 (2002)CrossRefGoogle Scholar
- 5.Lin, C.: The freight routing problem of time-definitive freight delivery common carriers. Transp. Res. Part B Methodol. 35(6), 525–547 (2001)CrossRefGoogle Scholar
- 6.Shangyao, Y., Weishen, L., Maonan, C.: Production scheduling and truck dispatching of ready mixed concrete. Transp. Res. Part E 44, 164–179 (2008)Google Scholar
- 7.Dablanc, L.: Goods transport in large European cities: difficult to organize, difficult to modernize. Transp. Res. Part A 41, 280–285 (2007)Google Scholar
- 8.Jula, H., Dessouky, M., Ioannou, P., Chassiakos, A.: Container movement by trucks in metropolitan networks: modelling and optimization. Transp. Res. Part E 41, 235–259 (2005)CrossRefGoogle Scholar
- 9.Moura, J.L., Ibeas, A., dell’Olio, L.: Optimization-simulation model for planning supply transport to large infrastructure public works located in congested urban areas. Netw. Spat. Econ. 10(4), 487–507 (2008)Google Scholar
- 10.Romero, J.P., Moura, J.L., Ibeas, A., Benavente, J.: Car-bicycle combined model for planning bicycle sharing systems. Transp. Res. Board. 91st Annual Meeting No. 12-3062 (2012a)Google Scholar
- 11.Romero, J.P., Ibeas, A., Moura, J.L., Benavente, J., Alonso, A.: A simulation-optimization approach to design efficient systems of bike sharing. Procedia—Soc. Behav. Sci. 54, 646–655 (2012b)Google Scholar
- 12.IDAE: Guía para la estimación del Combustible en las Flotas de Transporte por Carretera (2006)Google Scholar
- 13.IDAE: Guía de Vehículos Turismo de venta en España, con indicación de consumos y emisiones de CO2 (2013)Google Scholar
- 14.Ntziachristos, L.: 1.A.3.b. Road Transport TFEIP endorsed draft. Emision Inventory Guidebook (2009)Google Scholar