Decision model for siting transport and logistic facilities in urban environments: A methodological approach

Abstract

Please cite this article as: A. Fraile, E. Larrodé, .A. Magreñán, J.A. Sicilia, Decision model for siting transport and logistic facilities in urban environments: A methodological approach, Journal of Computational and Applied Mathematics (2014), http://dx. AbstractThe aim of this paper is to define a decision model that allow, through a Geographic Information System (GIS) to determine in an urban setting, the possible optimal locations of various facilities that would make up a new use for the transport infrastructure or logistics sector. The proposed methodology is based on the superposition of layers in a GIS software, enabling prioritization or exclusion of certain areas depending on whether or not meet certain requirements defined in each of these layers. The formulation used assigns each area of the map one degree of decision which classified all areas the best solution for supporting the solution in the Jenks optimization method. Five case studies of transportrelated facilities and as an example the location of a hydrogen refuelling station is solved taking into account the proposed methodology.

Mathematical modeling and computational methods

“…Sicilia et al [39] present an optimization algorithm that consists of metaheuristic processes to solve the problem of the capillary distribution of goods in major urban areas taking into consideration: time windows, capacity constraints, compatibility between orders and vehicles, etc. In [40], A. Fraile et al propose a decision model that allows, through a Geographic Information System to determine in an urban setting, the possible optimal locations of various facilities that would make up a new use for the transport infrastructure or logistic sector. B. Royo et al provide in [41] a solution of the long distance routing problem to help pallet and package delivery companies to the decision making, considering a mixed delivery system to improve the use of resources.…”

Delimitation of Homogeneous Zones in Vineyards Using Geostatistics and Multivariate Analysis of Different Vegetation Indices

“…Thematic maps were then generated by importing the interpolated data into a Geographic Information System (GIS), using the QGIS 2.18.17 software (QGIS Development Team, 2016). The intervals for each variable (ρ and VI) were categorized into three classes, adopting the Jenks Optimization method as classification rule, which minimizes the intrinsic differences and maximizes the differences between classes (Fraile et al, 2016). An explanation of the classification procedure used in building choropleth maps according to the Jenks Optimization, and its comparison to other methods, can be found in Ramos et al (2016).…”

Effects of Size and Sampling Grid on the Quality of Apparent Soil Electrical Conductivity Maps

“…The data that presented spatial dependence, i.e., did not present a pure nugget effect (PNE) in the semivariogram analysis, were interpolated by ordinary kriging. Then, spatial distribution ECa maps were generated with three classes of values (high, moderate, and low) determined by the Jenks optimization method, which minimizes the differences between intraclass values and maximizes the differences between classes (Fraile et al, 2016). The calculation of the experimental semivariograms, the fittingof the respective theoretical models, cross-validation, and the interpolation of the data were performed using the GS + 7.0 software and the RMSE calculation was conducted with the R 3.3.3 software (R Core Team, 2017).…”