BUSCADOR RECOLECTA

[EN] This research concerns multi-criteria vehicle routing problems. Mathematical models are formulated with mixed-integer programming. We consider maximization of capacity of truck vs. minimization of utilization of fuel, carbon emission and production of noise. The problems deal with green logistics for routes crossing the Western Pyrenees in Navarre, Basque Country and La Rioja, Spain.

We consider heterogeneous fleet of trucks. Different types of trucks have not only different capacities, but also require different amounts of fuel for operations. Consequently, the amount of carbon emission and noise vary as well. Companies planning delivery routes must consider the trade-off between the financial and environmental aspects of transportation. Efficiency of delivery routes is impacted by truck size and the possibility of dividing long delivery routes into smaller ones.

The results of computational experiments modeled after real data from a Spanish food distribution company are reported. Computational results based on formulated optimization models show some balance between fleet size, truck types, utilization of fuel, carbon emission and production of noise. As a result, the company could consider a mixture of trucks sizes and divided routes for smaller trucks. Analyses of obtained results could help logistics managers lead the initiative in environmental conservation by saving fuel and consequently minimizing pollution., This work has been partially supported by the National Research Center (NCN), Poland (DEC2013/11/B/ST8/04458),
by AGH, and by the Spanish Ministry of Economy and Competitiveness (TRA2013-48180-
C3-P and TRA2015-71883-REDT), and the Ibero-American Program for Science and Technology for Development
(CYTED2014-515RT0489). Likewise, we want to acknowledge the support received by the CAN Foundation in
Navarre, Spain (Grants CAN2014-3758 and CAN2015-70473). The authors are grateful to anonymous reviewers for
their comments.

[EN] Since its appearance in the 1990s, horizontal collaboration (HC) practices have revealed themselves as catalyzers for optimizing the distribution of goods in freight transport logistics. After introducing the main concepts related to HC, this paper offers a literature review on the topic and provides a classification of best practices in HC. Then, the paper analyses the main benefits and optimization challenges associated with the use of HC at the strategic, tactical, and operational levels. Emerging trends such as the concept of ` green' or environmentally- friendly HC in freight transport logistics are also introduced. Finally, the paper discusses the need of using hybrid optimization methods, such as simheuristics and learnheuristics, in solving some of the previously identified challenges in real- life scenarios dominated by uncertainty and dynamic conditions., This work has been partially supported by the Spanish Ministry of Economy and Competitiveness & FEDER (TRA2013-48180-C3-P, TRA2015-71883-REDT), The Erasmus+ program (2016-1-ES01-KA108-023465), the Ibero American Program of Science and Technology for Development (CYTED2014-515RT-0489), the CAN Foundation (CAN2014-3758, CAN2015-70473), and the Spanish Ministry of Education (FPU-14/00024).

[EN] This research presents the group of green vehicle routing problems with environmental costs translated into money versus production of noise, pollution and fuel consumption. This research is focused on multi-objective green logistics optimization. Optimality criteria are environmental costs: minimization of amount of money paid as externality cost for noise, pollution and costs of fuel versus minimization of noise, pollution and fuel consumption themselves. Some mixed integer programming formulations of multi-criteria vehicle routing problems have been considered. Mathematical models were formulated under assumption of existence of asymmetric distance-based costs and use of homogeneous fleet. The exact solution methods are applied for finding optimal solutions. The software used to solve these models is the CPLEX solver with AMPL programming language. The researchers were able to use real data from a Spanish company of groceries. Problems deal with green logistics for routes crossing the Spanish regions of Navarre, Basque Country and La Rioja. Analyses of obtained results could help logistics managers to lead the initiative in area of green logistics by saving money paid for environmental costs as well as direct cost of fuel and minimization of pollution and noise., This work has been partially supported by the National Research Center (NCN), Poland (DEC-2013/11/B/ST8/04458), by AGH, and by the Spanish Ministry of Economy and Competitiveness (TRA2013-48180-C3-P and TRA2015-71883-REDT), and the Ibero-American Program for Science and Technology for Development (CYTED2014-515RT0489). Likewise, we want to acknowledge the support received by the CAN Foundation in Navarre, Spain (Grants CAN2014-3758 and CAN2015-70473)

Trabajo presentado a la 13th Conference on Transport Engineering, CIT 2018. Gijón, 6-8 de junio de 2018., The city of Pamplona, in Spain, is currently experiencing several changes regarding sustainable mobility such as pedestrianization of some streets in the city center, and access control to the Old Town for motor vehicles through the use of automatic number-plate recognition. However, some groups including local neighbors and businesses are raising complaints as they are being affected by these measures. This is also the case for couriers and logistics companies which have now to comply with new regulations regarding delivery routes throughout the Old Town. This paper will present a comprehensive study of the situation that is being carried out, and in which social perceptions and freight traffic patterns in the Old Town of Pamplona are analyzed to understand how urban freight distribution could be improved in the area. For this purpose, we make use of a survey-based research to the stakeholders, i.e. pedestrians, logistics companies, retailers, and authorities of Pamplona. Results highlight pollution derived from transportation, lack of parking spaces as well as invasion of public spaces in the city center as the key issues for improving freight transportation in the Old Town. Finally, placing a distribution center in the Old Town and the promotion of the cycle-logistics are considered as the future of the urban distribution in Pamplona., This work has been partially supported by the Spanish Ministry of Economy and Competitiveness (TRA2013-48180-C3-P and TRA2015-71883-REDT), FEDER, and the Ibero-American Program for Science and Technology for Development (CYTED2014-515RT0489). Moreover, we appreciate the financial support of the Erasmus+ Program (2016-1-ES01-KA108-023465) and the CAN Foundation in Navarre, Spain (Grant CAN2017-6101). Likewise, we want to acknowledge the financial support received by Spanish Ministry of Education (Grant FPU 2014-0024).

We study the problem of optimization of trajectories for a robotic manipulator, with two degrees of freedom, which is constrained to pass through a set of waypoints in the workspace. The aim is to determine the optimal sequence of points and continuous optimal system trajectory. The actual formulation involves an optimal control problem of a dynamic system within integer variables that model the waypoints constrains. The nature of this problem, highly nonlinear and combinatorial, makes it particularly difficult to solve. The proposed method combines a meta-heuristic algorithm to determine the promising sequence of discrete points with a collocation technique to optimize the continuous path of the system. This method does not guarantee the global optimum, but can solve instances of dozens of points in reasonable computation time., This work has been partially supported by the Spanish Ministry of Economy and Competitiveness (TRA2013-48180-C3-P and TRA2015-71883-REDT), FEDER, and the Catalan Government (2014-CTP-00001).

20th EURO Working Group on Transportation Meeting, EWGT 2017, 4-6 September 2017, Budapest, Hungary, This research concerns multi-criteria vehicle routing problems. Mathematical models are formulated with mixed-integer programming. We consider maximization of capacity of truck vs. minimization of utilization of fuel, carbon emission and production of noise. The problems deal with green logistics for routes crossing the Western Pyrenees in Navarre, Basque Country and La Rioja, Spain.We consider heterogeneous fleet of trucks. Different types of trucks have not only different capacities, but also require different amounts of fuel for operations. Consequently, the amount of carbon emission and noise vary as well. Companies planningdelivery routes must consider the trade-off between the financial and environmental aspects of transportation. Efficiency of delivery routes is impacted by truck size and the possibility of dividing long delivery routes into smaller ones. The results of computational experiments modeled after real data from a Spanish food distribution company are reported. Computational results based on formulated optimization models show some balance between fleet size, truck types, utilization of fuel, carbon emission and production of noise. As a result, the company could consider a mixture of trucks sizes and divided routes for smaller trucks. Analyses of obtained results could help logistics managers lead the initiative in environmental conservation by saving fuel and consequently minimizing pollution., This work has been partially supported by the National Research Center (NCN), Poland (DEC-2013/11/B/ST8/04458), by AGH, and by the Spanish Ministry of Economy and Competitiveness (TRA2013-48180-C3-P and TRA2015-71883-REDT), and the Ibero-American Program for Science and Technology for Development (CYTED2014-515RT0489). Likewise, we want to acknowledge the support received by the CAN Foundation in Navarre, Spain (Grants CAN2014-3758 and CAN2015-70473).

We designed a survey that aims at estimating individual willingness-to-pay to reduce noise and air pollution arising from transportation activity near the Pyrenees in Navarre (Spain). Our participants cope with a series of contingent valuation questions and also with an economic experiment with real incentives about the same topic. Our goal is to identify several methodological problems in the valuation process coming from hypothetical bias, correlation effect and sequence effect when series of responses are requested. Our main results are that hypothetical bias is significant, because the willingness-to-pay is greater when the survey is hypothetical compared to when there is real monetary incentive. Likewise, the correlation effect also observes the same behavior since the willingness-to-pay for pollution mitigation is close to the one established for noise reduction. Finally, we have obtained mixed evidence for the sequence effect, being present only in the contingent valuation survey part., This work has been partially supported by the financial support of the Erasmus + Program (2019-I-ES01-KA103-062602), the Spanish Ministry of Economy and Competitiveness (TRA2013-48180-C3-P) and the Spanish Ministry of Science, Innovation, and Universities (RED2018-102642-T). Support received from the CAN Foundation in Navarre, Spain (Grant ID 903616 100010434 under the agreement LCF/PR/PR15/51100007).

The estimation of the noise impact caused by road freight transportation is critical to have acknowledgment of the ambiance pollution caused by road traffic crossing geographical areas containing important natural resources. Thus, our work proposes a within-subject survey where a Contingent Valuation Method (CVM) is combined with a laboratory economic experimental auction. Our study objective is to measure the willingness-to-pay (WTP) for reducing traffic noise nuisances due to freight transportation in the region of Navarre, Spain. A special focus is made regarding the measurement of the hypothetical bias, when a comparison is done between hypothetical WTP, coming from the CVM study, with real-incentivized one, as the outcome of the economic experiment. Additionally, statistical analyses are conducted in order to find explanation factors for these outcomes. Results suggest a strong evidence for an upward hypothetical bias (from 50% to 160%) indicating the income, the educational level, the gender, and the age as the main factors which explain that bias., This work has been partially supported by the Spanish Ministry of Economy and Competitiveness (TRA2013-48180-C3-P and TRA2015-71883-REDT), and the Ibero-American Program for Science and Technology for Development (CYTED2014-515RT0489). Likewise, the authors want to acknowledge the support received by CAN Foundation in Navarre, Spain (Grant CAN2015-70473).

Road transportation constitutes a key sector in developed countries, as an essential catalyst for economic and social activities. Nevertheless, it is relevant to emphasize the negative impacts of this activity identified in Economics as negative externalities. At the European Union, road transportation is the main cause of the air pollution impact on the population. Thus, this study explores the factors that influence the willingness to pay (WTP) on behalf of the citizens to reduce air pollution generated by road transport. In doing so, we propose two fundamental theoretical frameworks to explain individual behavior towards the environment actions: the Theory of Planned Behavior (TPB) and the Value-Belief-Norm (VBN) models. A questionnaire survey with 1,612 residents was used to collect data in
65 localities located in the Spanish Pyrenees and performing a statistical analysis with the resulting data relied on application of Structural Equation Models (SEM). Moreover, the survey results highlight the importance of psychological aspects as predictors of proenvironmental behaviors. Our empirical results provide a novel contribution about how governments and educational policies can enhance the positive attitude towards environmental actions, unifying the struggle in favor of environmental protection from early childhood., This work has been partly supported by the Spanish Ministry of Economy and Competitiveness (TRA2010-21644-C03-01, TRA2013-48180-C3-P, TRA2015-71883-REDT and ECO2017-86305-C4-4-R (AEI /FEDER, EU), and the Ibero-American Program for Science and Technology for Development (CYTED2014-515RT0489). We also want to acknowledge the support received from the CAN Foundation in Navarre, Spain (Grant ID 903 100010434 under the agreement LCF/PR/PR15/51100007).

Since its appearance in the 1990s, horizontal collaboration (HC) practices have revealed them-selves as catalyzers for optimizing the distribution of goods in freight transport logistics. After introducing the main concepts related to HC, this paper offers a literature review on the topic and provides a classification of best practices in HC. Then, the paper analyses the main benefits and optimization challenges associated with the use of HC at the strategic, tactical, and operational levels. Emerging trends such as the concept of ‘green’ or environmentally-friendly HC in freighttransport logistics are also introduced. Finally, the paper discusses the need of using hybrid optimization methods, such as simheuristics and learnheuristics, in solving some of the previously identified challenges in real-life scenarios dominated by uncertainty and dynamic conditions., This work has been partially supported by the Spanish Ministry of Economy and Competitiveness & FEDER (TRA2013-48180-C3-P, TRA2015-71883-REDT), The Erasmus+ program (2016-1-ES01-KA108-023465), the Ibero American Program of Science and Technology for Development (CYTED2014-515RT-0489), the CAN Foundation (CAN2014-3758, CAN2015-70473), and the SpanishMinistry of Education (FPU-14/00024).

Biofuels are emerging as a prominent renewable and sustainable energy sources in developed countries. In this sense, this paper presents a case study in which a biorefinery has to be sited in Northern Spain. Thus, the strategic decision of locating such a facility is deeply investigated through strategic policy evaluation. Then, tactical decisions ranging from purchasing and transportation policies to storage protocols are carried out. Only local and limited biomass can be harvested for supplying the biorefinery through a heterogeneous vehicle fleet. Moreover two different and mutually exclusive storage strategies are evaluated: direct supply from crops to biorefinery and using intermediate-collectors. Additionally, crop exploitation factors and biorefinery sizes are used to generate several scenarios in which the strategic decision of location as well as all the tactic decisions are made. Some mixed integer linear programming models are proposed to figure out all relevant decision problems. The results suggest that the Northwest study area as the best option to locate the biorefinery and recommend the intermediate-collector storage strategy. Moreover, the key information about critical biomass, crops and times are also provided., This work has been partially supported by the Government of Navarre (Biorefinery Navarra project IIM14196.RI1), the Spanish Ministry of Economy and Competitiveness (TRA2013-48180-C3-P and TRA2015-71883-REDT), and the Ibero-American Program for Science and Technology for Development (CYTED2014-515RT0489). Likewise, we want to acknowledge the support received by the CAN Foundation in Navarre, Spain (Grant CAN2017-6101).

Despite its negative impacts, freight transportation is a primary component of all supply chains. Decision makers have considered diverse strategies, such as Horizontal Collaboration (HC) and the usage of alternative types of vehicles, to reduce overall cost and the related environmental and social impacts. This paper assesses the implementation of an electric fleet of vehicles in urban goods distribution under HC strategy between carriers. A biased randomisation based algorithm is used to solve the problem with a multi-objective function to explore the relationships between both delivery and environmental costs. Real data from the city of Bogota, Colombia are used to validate this approach. Experiments with different costs and demands projections are performed to analyse short- and medium-term impacts related to the usage of electric vehicles in collaborative networks. Results show that the optimal selection of vehicle types depends considerably on the time horizon evaluation and demand variation., This work has been partially supported by the Spanish Ministry of Economy and Competitiveness (TRA2013-48180-C3-P and TRA2015-71883-REDT) and the Ibero-American Program for Science and Technology for Development (CYTED2014-515RT0489). Likewise, we want to acknowledge the support received by the Special Patrimonial Fund from Universidad de La Sabana (Colombia) and the doctoral grant from the UOC-Open University of Catalonia (Spain).

Incluye correcciones [Energies 2016, 9(7), 546; doi:10.3390/en9070546], Current logistics and transportation (L&T) systems include heterogeneous fleets consisting of common internal combustion engine vehicles as well as other types of vehicles using “green” technologies, e.g., plug-in hybrid electric vehicles and electric vehicles (EVs). However, the incorporation of EVs in L&T activities also raise some additional challenges from the strategic, planning, and operational perspectives. For instance, smart cities are required to provide recharge stations for electric-based vehicles, meaning that investment decisions need to be made about the number, location, and capacity of these stations. Similarly, the limited driving-range capabilities of EVs, which are restricted by the amount of electricity stored in their batteries, impose non-trivial additional constraints when designing efficient distribution routes. Accordingly, this paper identifies and reviews several open research challenges related to the introduction of EVs in L&T activities, including: (a) environmental-related issues; and (b) strategic, planning and operational issues associated with “standard” EVs and with hydrogen-based EVs. The paper also analyzes how the introduction of EVs in L&T systems generates new variants of the well-known Vehicle Routing Problem, one of the most studied optimization problems in the L&T field, and proposes the use of metaheuristics and simheuristics as the most efficient way to deal with these complex optimization problems., This work has been partially supported by the Spanish Ministry of Economy and Competitiveness (TRA2013-48180-C3-P and TRA2015-71883-REDT), FEDER, and the CYTED Program (CYTED2014-515RT0489). Likewise, we want to acknowledge the support received by the Catalan Government (2014-CTP-00001) and the CAN Foundation (CAN2014-3758 and CAN2015-70473).

20th EURO Working Group on Transportation Meeting, EWGT 2017, 4-6 September 2017, Budapest, Hungary, People living close to main roads may suffer from the nuisance of traffic and noise pollution. This paper assesses the effect of full routing cost in vehicle routing decisions by internalizing the external cost of noise. On a first step, noise externalities are economically assessed through a contingent valuation procedure. Secondly, a novel methodology is proposed to allocate the external costs to the road network links. Results show significant differences in routing planning depending on the approach: minimization of traditional internal cost versus minimization of full cost. These results encourage further research in pricing and methodologies to internalize externalities., This work has been partially supported by the Spanish Ministry of Economy and Competitiveness (TRA2013-48180-C3-P and TRA2015-71883-REDT), FEDER, and the Ibero-American Program for Science and Technology for Development (CYTED2014-515RT0489). Moreover, we appreciate the financial support of the Erasmus+ Program (2016-1-ES01-KA108-023465). Financial support from the Spanish Ministry of Education (FPU grant 14/00024) is gratefully acknowledged

Ponencia presentada al 19th EURO Working Group on Transportation Meeting, EWGT2016, 5-7 septiembre de 2016, Estambul (Turquía), Facilities location is a strategic decision which has to be carefully considered because it could involve the failure or success of a
business. For that reason, anything that helps decision makers to facilitate their location decision processes is of their utmost
interest. The aim of this paper is, therefore, providing a methodology that could be useful for the decision makers by giving them
not only an optimal point but also a whole region where they can focus on their attention. Knowing that biofuels are settling as a
new alternative energy source which has been spreading around the world to reduce greenhouse gas emissions and oil
dependence, this methodology is tested in the real case of locating a biorefinery in Navarre, Spain. Moreover, A Mixed Integer
Linear Programming (MILP) model has been developed to generate optimal region vertices as well as some other supply chain
characteristics, including, among others, which crops are going to be harvested, when they are going to be collected, and their
storage levels. Additionally, two criteria were implemented in MILP model to create two optimal regions: one considering an
economic criterion and other one minimizing environmental impact. As a result, two regions were drawn in the Navarrese
territory that point out where a biorefinery should be located and how the supply chain should be designed., This work has been partially supported by the Government of Navarre (Biorefinery Navarra project IIM14196.RI1) the Spanish Ministry of Economy and Competitiveness (TRA2013-48180-C3-P and TRA2015-71883-REDT), and the Ibero-American Program for Science and Technology for Development (CYTED2014-515RT0489). Likewise, we want to acknowledge the support received by the CAN Foundation in Navarre, Spain (Grant CAN2015-70473).

Road freight transportation includes various internal and external costs that need to be accounted for in the construction of efficient routing plans. Typically, the resulting optimization problem is formulated as a vehicle routing problem in any of its variants. While the traditional focus of the vehicle routing problem was the minimization of internal routing costs such as travel distance or duration, numerous approaches to include external factors related to environmental routing aspects have been recently discussed in the literature. However, internal and external routing costs are often treated as competing objectives. This paper discusses the internalization of external routing costs through the consideration of green taxes and green tolls. Numeric experiments with a biased-randomization savings algorithm, show benefits of combining internal and external costs in delivery route planning., This work has been partially supported by the Spanish Ministry of Economy and Competitiveness (TRA2013-48180-C3-P and TRA2015-71883-REDT), FEDER, and the Ibero-American Program for Science and Technology for Development (CYTED2014-515RT0489). Moreover, the authors appreciate the financial support of the Erasmus+ Program (2016-1-ES01-KA108-023465) and the CAN Foundation in Navarre, Spain (Grant CAN2017-6101). Likewise, we want to acknowledge the financial support received by Spanish Ministry of Education (Grant FPU 2014-0024).

Esta tesis doctoral investiga el uso de técnicas de modelización y simulación en áreas urbanas de ciudades inteligentes, explorando a su vez cómo el big data puede usarse para alimentar estos modelos. Estas técnicas de modelización se han aplicado a dos campos diferentes que han ganado importancia durante los últimos años pero donde la investigación es aún limitada: logística urbana y resiliencia urbana. A través de esta tesis, el autor ha ampliado el conocimiento en estos campos mediante la exploración de diferentes métodos como metaheurísticas, modelización de transporte y simulación basada en agentes de cara a definir nuevas metodologías que se pueden aplicar en áreas urbanas. En relación al campo de la logística, el autor ha demostrado mediante el uso de metaheurísticas que cuando se considera la congestión del tráfico como un atributo dinámico para optimizar las rutas de reparto en áreas urbanas, el tiempo de reparto puede reducirse en un 11%, lo cual es crucial para las empresas de logística en un mercado que es más feroz cada día. Esto es cierto no solo para áreas urbanas, sino que también se ha demostrado que optimizar rutas considerando la congestión del tráfico también es beneficioso a nivel estratégico para las rutas entre ciudades. Para considerar los costes de congestión en tiempo real, se ha desarrollado un nuevo enfoque en el que se descargan datos de Google para alimentar estos modelos metaheurísticos, aunque también se podrían utilizar otras fuentes de big data. En esta tesis también se presenta una metodología que se ha implementado para modelar rutas logísticas en áreas urbanas considerando datos en tiempo real y con la flexibilidad de agregar diferentes atributos de red (gradiente, direcciones prohibidas, CO2, etc.) de cara a simular diferentes escenarios. Esto puede ser útil para que las empresas de logística optimicen sus entregas (eligiendo entre furgoneta o triciclo, seleccionando la hora del día para entregar, etc.) pero también para servir a las autoridades públicas de guía en materia de políticas urbanas y de transporte (peatonalización de algunas calles, prohibiciones de tráfico, etc.). En cuanto a la resiliencia urbana, la tesis se centra en la planificación de la evacuación. Se ha creado una nueva metodología en la que se utiliza la simulación basada en agentes a través de submodelos interconectados para modelar un escenario de evacuación a gran escala (evento de inundación como consecuencia del colapso de una presa). Esta investigación define los datos necesarios para crear estos modelos que pueden ser de gran ayuda para mejorar la resiliencia de las ciudades, y también analiza cómo la congestión del tráfico puede afectar los procedimientos de evacuación. A través de los diferentes artículos de investigación que componen esta tesis, el autor aporta luz a estas cuestiones mediante el desarrollo de nuevas metodologías y el uso de casos de estudio reales con el objetivo de ayudar a planificadores urbanos, empresas y responsables políticos a crear ciudades inteligentes más eficientes, sostenibles y resilientes., This thesis investigates the use of modelling and simulation techniques in urban areas of smart cities, also exploring how big data can be used to feed these models. These modelling techniques have been applied to two different fields that have been gaining prominence during the last years but where research is still limited: urban logistics and urban resilience. Through this thesis, the author has expanded the research knowledge in these fields by exploring different methods such as meta-heuristics, transport modelling, and agent-based simulation in order to define new methodologies to be applied to urban areas. Regarding logistics, the author has shown through the use of meta-heuristics that when traffic congestion is considered as a dynamic attribute to optimize delivery routes in urban areas, time can be reduced by 11%, which is crucial for logistics companies in a market that is fiercer every day. This is true not only for urban areas, but this research has also demonstrated that optimizing routes with dynamic congestion attributes is also beneficial at a strategic level for routes between cities. To consider congestion costs in real time, a new approach has been developed in which data from Google is downloaded to feed these meta-heuristic models, although other sources of big data could be also used. In this thesis, a methodology is also presented that has been used to model logistics routes in urban areas considering real-time data and with the flexibility to add different network attributes (gradient, traffic bans, CO2, etc.) to simulate different scenarios. This can be useful for logistics companies to optimize their deliveries (choosing between van or tricycles, selecting the time of the day to deliver, etc.) but also for public authorities to get guidance on different transport and urban policies (pedestrianization of some streets, traffic bans, etc.).As for city resilience, the thesis focuses on evacuation planning. A new methodology has been created in which agent-based simulation is used through interconnected sub-models to model a large-scenario evacuation scenario (flooding event as a consequence of a dam collapse). This research defines the data needed to create these models that can be of great help to improve city resilience, and also analyzes how traffic congestion can affect the evacuation procedures. Through the different research articles that compose this thesis, the author brings light to these fields by developing new methodologies and using real case-studies that can help urban planners, companies, and policy makers to create more efficient, sustainable, and resilient smart cities., TRA2015-71883-REDT. Transport, Logistics, and Smart Production. Spanish Ministry of Economics and Competitiveness; CYTED2014-P514RT0013. Ibero-American Network for Smart Logistics and Sustainable Transportation in Urban Environments. Ibero-American Program for Science and Technology for Development; TRA2013-48180-C3-1-P. Horizontal Cooperation and Environmental Costs in the Management of Sustainable Road Freight Transportation. Spanish Ministry of Economics and Competitiveness. The attendance to conferences has been financially supported by the DECYL Research Group and EDONA, from the Public University of Navarre., Programa de Doctorado en Ciencias y Tecnologías Industriales (RD 99/2011), Industria Zientzietako eta Teknologietako Doktoretza Programa (ED 99/2011)

Many combinatorial optimization problems (COPs) encountered in real-world logistics, transportation,
production, healthcare, financial, telecommunication, and computing applications are NP-hard in nature.
These real-life COPs are frequently characterized by their large-scale sizes and the need for obtaining
high-quality solutions in short computing times, thus requiring the use of metaheuristic algorithms. Metaheuristics
benefit from different random-search and parallelization paradigms, but they frequently assume
that the problem inputs, the underlying objective function, and the set of optimization constraints
are deterministic. However, uncertainty is all around us, which often makes deterministic models oversimplified
versions of real-life systems. After completing an extensive review of related work, this paper
describes a general methodology that allows for extending metaheuristics through simulation to solve
stochastic COPs. ‘Simheuristics’ allow modelers for dealing with real-life uncertainty in a natural way by
integrating simulation (in any of its variants) into a metaheuristic-driven framework. These optimization-driven
algorithms rely on the fact that efficient metaheuristics already exist for the deterministic version
of the corresponding COP. Simheuristics also facilitate the introduction of risk and/or reliability analysis
criteria during the assessment of alternative high-quality solutions to stochastic COPs. Several examples
of applications in different fields illustrate the potential of the proposed methodology., This work has been partially supported by the Spanish Ministry
of Economy and Competitiveness (grant TRA2013-48180-C3-P),
FEDER, and the Ibero-American Programme for Science and
Technology for Development (CYTED2014-515RT0489). Likewise
we want to acknowledge the support received by the Department
of Universities, Research & Information Society of the Catalan
Government (Grant 2014-CTP-00001) and the CAN Foundation
(Navarre, Spain) (Grant 3CAN2014-3758).

Ponencia presentada al 19th EURO Working Group on Transportation Meeting, EWGT2016, 5-7 septiembre de 2016, Estambul (Turquía), This research presents the group of green vehicle routing problems with environmental costs translated into money versus production of noise, pollution and fuel consumption. This research is focused on multi-objective green logistics optimization. Optimality criteria are environmental costs: minimization of amount of money paid as externality cost for noise, pollution and costs of fuel versus minimization of noise, pollution and fuel consumption themselves. Some mixed integer programming formulations of multi-criteria vehicle routing problems have been considered. Mathematical models were formulated under assumption of existence of asymmetric distance-based costs and use of homogeneous fleet. The exact solution methods are applied for finding optimal solutions. The software used to solve these models is the CPLEX solver with AMPL programming language. The researchers were able to use real data from a Spanish company of groceries. Problems deal with green logistics for routes crossing the Spanish regions of Navarre, Basque Country and La Rioja. Analyses of obtained results could help logistics managers to lead the initiative in area of green logistics by saving money paid for environmental costs as well as direct cost of fuel and minimization of pollution and noise., This work has been partially supported by the National Research Center (NCN), Poland
(DEC-2013/11/B/ST8/04458), by AGH, and by the Spanish Ministry of Economy and
Competitiveness (TRA2013-48180-C3-P and TRA2015-71883-REDT), and the Ibero-American Program for Science and Technology for Development (CYTED2014-515RT0489). Likewise,
we want to acknowledge the support received by the CAN Foundation in Navarre, Spain (Grants
CAN2014-3758 and CAN2015-70473).