Open Access
Topology effects in drone parcel delivery
(Cal-Tek srl, 2024) Izco Berastegui, Irene; Serrano Hernández, Adrián; Faulín Fajardo, Javier; Institute of Smart Cities - ISC; Universidad Pública de Navarra / Nafarroako Unibertsitate Publikoa, PJUPNA26-2022
Despite the positive sustainability prospects of drones, their flight range is compromised due to their limited battery capacity and the payload of delivered parcels. An alternative to address this challenge is the placement of charging stations where drone batteries are recharged to expand their flying range. The aim of this work is determining the number and location of drone charging stations for topology-dependent scenarios: rural areas and densely populated urban areas. To the best of the researchers' knowledge, there is currently no existing study in the literature that specifically investigates the impacts of topology on drone-assisted delivery. This study focuses on designing drone assignment strategies through optimization-simulation, aiming at minimizing charging station installation costs and operational costs and as a novelty, drone battery consumption is considered in the model design. Drone delivery order instances with different sizes and spatial distributions are generated to simulate realistic scenarios of demand and evaluate the optimization model to allocate the customer demands to stations and dimensioning drones fleet. Results show that considering parcel weight and flight distance has a significant impact on the performance of drone allocation to stations and highlight the effects of topology in the implementation of a drone-assisted delivery network.
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
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
Exploring crowdshippers' behavior and preferences: intertwining urban distribution and people mobility
(Elsevier, 2025-05-14) García Herrera, Alisson Maurinne; Serrano Hernández, Adrián; Faulín Fajardo, Javier; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Institute of Smart Cities - ISC; Gobierno de Navarra / Nafarroako Gobernua
Collaborative economy companies in the transport field have been a disruptive force in the urban mobility landscape around the world during the last decade 2010-2020. Crowdshipping has emerged as a collaborative economy option promoting improved utilization of currently underutilized transportation capacity, thereby reducing transportation costs and emissions. This article aims to analyze and synthesize existing research on the impact of the crowdshipper (individuals responsible for collecting and delivering the product) behavior on the system and the factors that drive his or her willingness to participate, to identify best practices and opportunities to enhance business analytics, decision-making, and model efficiency in this emerging area.
Open Access
A strategic multistage tactical two-stage stochastic optimization model for the airline fleet management problem
(Elsevier, 2020) Serrano Hernández, Adrián; Cadarso, Luis; Faulín Fajardo, Javier; Institute of Smart Cities - ISC
This work proposes stochastic optimization for the airline fleet management problem, considering uncertainty in the demand, operational costs, and fares. In particular, a multistage tree is proposed, compounded of strategic and tactical nodes. At the former ones, fleet composition decisions are made, while at the latter ones, aircraft assignment decisions are formulated. Computational experiments are based on a small air network with seven strategic nodes and fourteen tactical nodes (i.e., seasons) where two fleet types are available to be included: Airbus 320, and Boeing 737. These results provide the optimal fleet planning and assignment at both strategic and tactical scopes. Finally, it is shown the superior performance of the stochastic version of this problem against the deterministic one.
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
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.
Open Access
Optimizing freight delivery routes: the time-distance dilemma
(Elsevier, 2024-12-01) 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 optimizing freight delivery routes are based on minimizing a distance-based cost function. New approaches also use time as an objective function to minimize. However, the trade-off between time and distance is sometimes unclear. This paper presents a new approach to route optimization in which both time and distance are considered conjointly. For this purpose, the vehicle operating cost and the value of time have been used to translate time and distance into monetary units. By studying three different networks in Spain with varying levels of detail (the region of Catalonia, the city of Barcelona, and the Pamplona city center), the results show that minimizing both time and distance yield better results than the traditional approach, especially at a local level, where congestion effects are more relevant. These findings are helpful for logistics companies to optimize their operations, as well as for public authorities who could employ these models to make decisions and create policies on logistics.
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.