Open Access
Evaluación ponencias debate tren altas prestaciones
(2013) Faulín Fajardo, Javier
Open Access
Managing transportation externalities in the Pyrenees region: measuring the willingness-to-pay for road freight noise reduction using an experimental auction mechanism
(Elsevier, 2018) Denant-Boemont, Laurent; Faulín Fajardo, Javier; Hammiche, Sabrina; Serrano Hernández, Adrián; Estatistika, Informatika eta Matematika; Institute of Smart Cities - ISC; Estadística, Informática y Matemáticas
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.
Open Access
A review of simheuristics: extending metaheuristics to deal with stochastic combinatorial optimization problems
(Elsevier Ltd., 2015) Juan Pérez, Ángel Alejandro; Faulín Fajardo, Javier; Grasman, Scott Erwin; Rabe, Markus; Figueira, Gonçalo; Estadística e Investigación Operativa; Estatistika eta Ikerketa Operatiboa
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.
Open Access
The impact of integrating open data in smart last-mile logistics: the example of Pamplona open data catalog
(MDPI, 2025-01-08) Al-Rahamneh, Anas; Serrano Hernández, Adrián; Faulín Fajardo, Javier; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Institute of Smart Cities - ISC
Last-mile logistics is one of the most complicated operations in the whole logistic process. This concept describes the final leg of a product travel from a warehouse or hub to specific customers. One of the last-mile logistics challenges that courier delivery companies face is route planning. Ineffective route planning can cause operational delays that cascade and affect several last-mile deliveries. Thus, numerous factors need to be considered to plan and optimize effective delivery routes. These involve many extraordinary and unpredictable events, including weather, traffic conditions, and traffic regulations. A lack of accessible data hinders dynamic, efficient, and reliable route planning, leading to these factors being overlooked. In this paper, we propose the use of open data (OD) to overcome these limitations. OD are information available for anyone to access, reuse, and distribute for free with minimal attribution and sharing restrictions. Therefore, the aim of this work is to examine the impact of incorporating specific open data elements on the performance of the Clarke and Wright algorithm, particularly in calculating savings, and identifying optimal routes. The results we obtained showed the effect of considering OD with an increase rate of approximately 2% on the total distance compared to not considering them.
Open Access
Simheuristics: an introductory tutorial
(IEEE, 2022) Juan, Ángel A.; Li, Yuda; Ammouriova, Majsa; Panadero, Javier; Faulín Fajardo, Javier; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Institute of Smart Cities - ISC
Both manufacturing and service industries are subject to uncertainty. Probability techniques and simulation methods allow us to model and analyze complex systems in which stochastic uncertainty is present. When the goal is to optimize the performance of these stochastic systems, simulation by itself is not enough and it needs to be hybridized with optimization methods. Since many real-life optimization problems in the aforementioned industries are NP-hard and large scale, metaheuristic optimization algorithms are required. The simheuristics concept refers to the hybridization of simulation methods and metaheuristic algorithms. This paper provides an introductory tutorial to the concept of simheuristics, showing how it has been successfully employed in solving stochastic optimization problems in many application fields, from production logistics and transportation to telecommunication and insurance. Current research trends in the area of simheuristics, such as their combination with fuzzy logic techniques and machine learning methods, are also discussed.
Open Access
Selecting freight transportation modes in last-mile urban distribution in Pamplona (Spain): an option for drone delivery in smart cities
(MDPI, 2021) Serrano Hernández, Adrián; Ballano Biurrun, Aitor; Faulín Fajardo, Javier; Institute of Smart Cities - ISC; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Economía; Ekonomia
Urban distribution in medium-sized cities faces a major challenge, mainly when deliveries are difficult in the city center due to: an increase of e-commerce, weak public transportation system, and the promotion of urban sustainability plans. As a result, private cars, public transportation, and freight transportation compete for the same space. This paper analyses the current state for freight logistics in the city center of Pamplona (Spain) and proposes alternative transportation routes and transportation modes in the last-mile city center distribution according to different criteria evaluated by residents. An analytic hierarchy process (AHP) was developed. A number of alternatives have been assessed considering routes and transportation modes: the shortest route criterion and avoiding some city center area policies are combined with traditional van-based, bike, and aerial (drone) distribution protocols for delivering parcels and bar/restaurant supplies. These alternatives have been evaluated within a multicriteria framework in which economic, environmental, and social objectives are considered at the same time. The point in this multicriteria framework is that the criteria/alternative AHP weights and priorities have been set according to a survey deployed in the city of Pamplona (Navarre, Spain). The survey and AHP results show the preference for the use of drone or bike distribution in city center in order to reduce social and environmental issues.
Open Access
A reliability-extended simheuristics for the sustainable vehicle routing problem with stochastic travel times and demands
(Springer, 2025-04-01) Abdullahi, Hassana; Reyes-Rubiano, Lorena Silvana; Ouelhadj, Djamila; Faulín Fajardo, Javier; Juan, Ángel A.; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Institute of Smart Cities - ISC; Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa
Real-life transport operations are often subject to uncertainties in travel time or customers'demands. Additionally, these uncertainties greatly impact the economic, environmental, and social costs of vehicle routing plans. Thus, analysing the sustainability costs of transportation activities and reliability in the presence of uncertainties is essential for decision makers. Accordingly, this paper addresses the Sustainable Vehicle Routing Problem with Stochastic Travel times and Demands. This paper proposes a novel weighted stochastic recourse model that models travel time and demand uncertainties. To solve this challenging problem, we propose an extended simheuristic that integrates reliability analysis to evaluate the reliability of the generated solutions in the presence of uncertainties. An extensive set of computational experiments is carried out to illustrate the potential of the proposed approach and analyse the influence of stochastic components on the different sustainability dimensions.
Open Access
Analysing capacity challenges in the Multi-Airport System of Mexico City
(Dime University of Genoa, 2022) Mújica Mota, Miguel; Faulín Fajardo, Javier; Izco Berastegui, Irene; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Institute of Smart Cities - ISC
The relentless growth in Mexico City’s aviation traffic has inevitably strained capacity development of its airport, raising the dilemma between the possible solutions. In the present study, Mexico’s Multi-Airport System is subjected to analysis by means of multi-model simulation, focusing on the capacity-demand problem of the system. The methodology combines phases of modelling, data collection, simulation, experimental design, and analysis. Drawing a distinction from previous works involving two-airport systems. It also explores the challenges raised by the Covid-19 pandemic in Mexico City airport operations, with a discrete-event simulation model of a multi-airport system composed by three airports (MEX, TLC, and the new airport NLU). The study is including the latest data of flights, infrastructures, and layout collected in 2021. Therefore, the paper aims to answer to the question of whether the system will be able to cope with the expected demand in a short-, medium-, and long term by simulating three future scenarios based on aviation forecasts. The study reveals potential limitations of the system as time evolves and the feasibility of a joint operation to absorb the demand in such a big region like Mexico City
Open Access
Valuations of transport nuisances and cognitive biases: a survey laboratory experiment in the Pyrenees region
(Springer, 2021) Denant-Boemont, Laurent; Faulín Fajardo, Javier; Hammiche, Sabrina; Serrano Hernández, Adrián; Estatistika, Informatika eta Matematika; Institute of Smart Cities - ISC; Estadística, Informática y Matemáticas
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.
Open Access
Understanding the dynamics of crowdshipping in last-mile distribution within urban mobility: a comprehensive framework
(Elsevier, 2025-10-01) García Herrera, Alisson Maurinne; Serrano Hernández, Adrián; Faulín Fajardo, Javier; Institute of Smart Cities - ISC; Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa; Gobierno de Navarra / Nafarroako Gobernua
Crowdshipping, a collaborative economy model that takes advantage of the crowd for the delivery of goods, promises to address the problems of urban logistics. This article integrates the literature to identify relevant factors that influence the success of crowdshipping, while addressing sustainability objectives. We use the PRISMA method, a widely recognized framework for systematic reviews that, by meeting high-quality standards, guarantees the reliability of the evidence. We systematically reviewed the literature to address three research questions: identifying factors that influence crowdshipping success, evaluating its contribution to sustainability goals, and evaluating the role of Operation Research (OR) in improving crowdshipping efficiency. Specifically, OR techniques offer significant potential for optimizing routing, matching supply and demand, and enhancing decision-making processes. Through this comprehensive and in-depth analysis, we provide information for future research, modeling, practical implementation, and potential policy recommendations.