In this paper we propose a fuzzy neural network prediction approach based on metaheuristics for container flow forecasting. The approach uses fuzzy if-then rules for selection between two different heuristics for developing neural network architecture, simulated annealing and genetic algorithm, respectively. These non-parametric models are compared with traditional parametric ARIMA technique. Time series composed from monthly container traffic observations for Port of Barcelona are used for model developing and testing. Models are compared based on the most important criteria for performance evaluation and for each of the data sets (total container traffic, loaded, unloaded, transit and empty) the appropriate model is selected.

The economics literature offers many examples of studies of the economic impact of transportation infrastructure such as highways, ports, and airports; however, little attention has been paid to other types of infrastructure such as logistics platforms. This article is a first assessment of the economic effects of the largest logistics platform in Europe Á PLAZA, the Zaragoza Logistics Platform Á located in Spain. More precisely, this paper analyzes the economic significance of PLAZA on the economy of the Aragon region where it is located. The methodology is based on the application of inputÁoutput analysis to the final demand of logistics platform-based companies in a manner that is similar to well-established studies of the economic impacts of tourism on tourist expenditure. This makes it possible to quantify the various levels of economic effects (direct, indirect, and induced) in terms of jobs, salaries, and wages, turnover, gross operating surplus (GOS), and gross value added (GVA). The conclusions reveal the economic importance PLAZA has for the regional economy of Aragon, representing just over 2% of total GVA and 3% of turnover.

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