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In this work, a depiction and analysis of the state of last mile logistics in Spain is presented. Through the study of the data from 12 Spanish provinces gathered by an IT service provider that enables the operation of 12 different carriers, the main characteristics of each region in Spain are analysed and discussed, portraying not only the geographical and demographic distinctions between the areas, but also the differences in operational efficiency between carriers. Furthermore, the posited metrics are collated with the population density indicators of the provinces, in an attempt to identify significant correlations and patterns that may bring light to the effect on the operation of the agencies of geographic concentration.

This paper deals with the optimisation of the operating costs in a distributed electric and heating energy generation network. The network considers different options to supply the electric and heating demand of a large consumer building: the electricity can be directly bought from the grid, can be taken from renewable energy sources or can be produced from gas using a combined heat and power system. In the same line, the heating can be taken from a thermal solar renewable system, from the boiler or from the combined heat and power system. In addition, the large consumer has batteries to store electricity excesses and thermal storage systems to store the heating excess. The multicommodity flow mathematical formulation of the problem couples both electric and thermal models by considering cogeneration systems. The model is solved by a particle swarm optimisation (PSO) algorithm that is compared to the optimal solutions provided by Gurobi optimisation commercial software and a Monte Carlo algorithm. The PSO algorithm proved a very efficient performance in the available short time to provide the energy commands to the systems outperforming the alternative approaches.

The use of multi-actor multi-criteria methodologies is widely accepted to evaluate city logistics policies and measures. We have applied this procedure to the proposal of implementation of two alternative measures in a fresh food market in the Seville city center, after gathering all the relevant data from a survey passed to the retailers working in the premises. After perceiving that the quantitative results did not provide an appropriate representation of the existing scenario, we segmented the carrier stakeholder group into two smaller independent groups, obtaining more homogeneous results in the quantitative analysis and a better representation of reality. The segmentation of stakeholder groups appears then as an interesting requirement for this type of analysis to better serve as a decision-making tool for policy implementations.

Choice design building based on D-error minimisation can be accomplished either by using predefined β values or by assuming probabilistic distributions for them. Several mathematical techniques have been used for both approaches in the past, resulting in algorithms that obtain efficient designs, which guarantee the high quality of the information that will be provided by the respondents. This paper proposes the use of a genetic algorithm for dealing with the problem of building designs with minimum D-error , describing the technique and applying it successfully to several benchmark cases. Design matrices, D-error values, percentages of level overlap and computation times are provided for each case.

The objective of this research is to advice the Municipality of The Hague whether, if and under which conditions, the implementation of an Urban Consolidation Centre (UCC) is possible and desirable. To determine factors that caused the success or failure of UCCs in practice, a survey of 6 cases in Europe is conducted. The cases were selected because of the similarity of the service area of the UCC and the city centre of The Hague or because of the uniqueness of the UCC. To determine the possible success for a UCC in The Hague four scenarios are evaluated. Two major difficulties with implementing the UCC are the allocation of the costs and benefits and the willingness to cooperate of the transportation companies. Both consignees and transportation companies can benefit financially from using the UCC. The UCC operator, however, incurs the costs. The municipality should play a role in bringing the costs and benefits together.

In medium and large cities, the delivery of goods represents a significant contribution to the problems of congestion, lack of parking, pollution and energy consumption. The characteristics of this type of transport are also very different from passenger mobility, even though they are often assimilated, due to the lack of specific tools for estimation and analysis, and also of indicators to evaluate improvements in the systems of urban goods distribution. In this work, we start by developing a systematic model to estimate the transport of goods in a city, according to the particularities of its supply and demand. This model can then be used to determine with a high level of detail the contribution of the delivery of goods to the ecological footprint of the city, thus proposed as the key indicator of the efficiency of this type of transport. The work is applied to the city of Seville, in Spain.

An improvement on drayage operations is necessary for intermodal freight transport to become competitive. When drayage takes place in cities or urban centres transit times are usually random, as a consequence finding the optimal fleet schedule is very difficult, and this schedule can even change during the day. The work we present here is a dynamic optimisation model which uses real-time knowledge of the fleet's position, permanently enabling the planner to reallocate tasks as the problem conditions change. Stochastic trip times are considered, both in the completion of each task and between tasks. Tasks can also be flexible or well-defined. We describe the algorithm in detail for a test problem and then apply it to a set of random drayage problems of different size and characteristics, obtaining significant cost reductions with respect to initial estimates.