Open Access
A biased-randomized learnheuristic for solving the team orienteering problem with dynamic rewards
(Elsevier, 2020) Reyes-Rubiano, Lorena Silvana; Juan Pérez, Ángel Alejandro; Bayliss, C.; Panadero, Javier; Faulín Fajardo, Javier; Copado, P.; Institute of Smart Cities - ISC
In this paper we discuss the team orienteering problem (TOP) with dynamic inputs. In the static version of the TOP, a fixed reward is obtained after visiting each node. Hence, given a limited fleet of vehicles and a threshold time, the goal is to design the set of routes that maximize the total reward collected. While this static version can be efficiently tackled using a biased-randomized heuristic (BR-H), dealing with the dynamic version requires extending the BR-H into a learnheuristic (BR-LH). With that purpose, a 'learning' (white-box) mechanism is incorporated to the heuristic in order to consider the variations in the observed rewards, which follow an unknown (black-box) pattern. In particular, we assume that: (i) each node in the network has a 'base' or standard reward value; and (ii) depending on the node's position inside its route, the actual reward value might differ from the base one according to the aforementioned unknown pattern. As new observations of this black-box pattern are obtained, the white-box mechanism generates better estimates for the actual rewards after each new decision. Accordingly, better solutions can be generated by using this predictive mechanism. Some numerical experiments contribute to illustrate these concepts.
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.
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
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
Integrating simulation and optimization: a case study in Pamplona for self-collection delivery points network design
(Cal-Tek, 2023) Izco Berastegui, Irene; Serrano Hernández, Adrián; Sawik, Bartosz; Faulín Fajardo, Javier; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Institute of Smart Cities - ISC; Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa, PJUPNA26-2022
The disruptions experienced by the processes in the last mile delivery during the SARS-CoV-2 pandemic raised the dilemma of up-to-date last mile approaches for Urban Logistics (UL) issues. Self-Collection Delivery Systems (SCDS) have been proved to be an improvement for all the players of the SC, providing flexibility of time-windows and reducing overall mileage, delivery time and, consequently, gas emissions. Differing from previous works involving hybrid modeling for automated parcel lockers (APL) network design, this paper brings a System Dynamics Simulation Model (SDSM) to forecast online shopping demand in the Spanish city of Pamplona. A bi-criteria Facility Location Problem (FLP) is solved by means of an e-constraint method, where e is defined as the level of coverage of the total demand. The experiment run considers 90% of demand coverage, in order to obtain the most complex network possible. The simulation and demand forecast was carried out using Anylogic simulation software and the optimization procedure makes use of the Java-based CPLEX API solver.
Open Access
Optimizing energy consumption in transportation: literature review, insights, and research opportunities
(MDPI, 2020) Corlu, Canan Gunes; Torre Martínez, Rocío de la; Serrano Hernández, Adrián; Juan Pérez, Ángel Alejandro; Faulín Fajardo, Javier; Institute for Advanced Research in Business and Economics - INARBE; Institute of Smart Cities - ISC
From airplanes to electric vehicles and trains, modern transportation systems require large quantities of energy. These vast amounts of energy have to be produced somewhere—ideally by using sustainable sources—and then brought to the transportation system. Energy is a scarce and costly resource, which cannot always be produced from renewable sources. Therefore, it is critical to consume energy as efficiently as possible, that is, transportation activities need to be carried out with an optimal intake of energetic means. This paper reviews existing work on the optimization of energy consumption in the area of transportation, including road freight, passenger rail, maritime, and air transportation modes. The paper also analyzes how optimization methods—of both exact and approximate nature—have been used to deal with these energy-optimization problems. Finally, it provides insights and discusses open research opportunities regarding the use of new intelligent algorithms—combining metaheuristics with simulation and machine learning—to improve the efficiency of energy consumption in transportation.
Open Access
An extended behavior model for explaining the willingness to pay to reduce the air pollution in road transportation
(Elsevier, 2021) Sánchez García, Mercedes; Zouaghi, Ferdaous; Lera López, Fernando; Faulín Fajardo, Javier; Enpresen Kudeaketa; Ekonomia; Estatistika, Informatika eta Matematika; Institute on Innovation and Sustainable Development in Food Chain - ISFOOD; Institute for Advanced Research in Business and Economics - INARBE; Institute of Smart Cities - ISC; Gestión de Empresas; Economía; Estadística, Informática y Matemáticas
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.
Open Access
Is time more important than distance to optimize freight delivery routes? An approach using the value of time
(Elsevier, 2024-02-23) Alvarez Indave, Pablo; Serrano Hernández, Adrián; Lerga Valencia, Iosu; Faulín Fajardo, Javier; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Institute of Smart Cities - ISC; Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa, PJUPNA26-2022
Traditional approaches to optimize freight delivery routes are based on minimizing a distance-based cost function. New approaches use also time as the objective function to minimize. However, the trade-off between time and distance is sometimes unclear. This paper presents a new approach to optimize delivery routes in which both time and distance are used together to optimize delivery routes. For this purpose, the operating cost of a vehicle and the value of time have been used to convert time and distance into monetary units. Through the study of three different networks in Spain with different level of detail (the region of Catalonia, the city of Barcelona, and the old part of Pamplona), the results have indicated that minimizing both time and distance provides better results than the traditional approach, especially at a local level where congestion effects are more relevant.
Open Access
Locating a biorefinery in Northern Spain: decision making and economic consequences
(Elsevier, 2019) Serrano Hernández, Adrián; Faulín Fajardo, Javier; Institute of Smart Cities - ISC; Gobierno de Navarra / Nafarroako Gobernua, IIM14196.RI1
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.