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
Multi-criteria optimization for fleet size with environmental aspects
(Elsevier, 2017) Sawik, Bartosz; Faulín Fajardo, Javier; Pérez Bernabeu, Elena; Institute of Smart Cities - ISC
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.
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
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
Evaluación ponencias debate tren altas prestaciones
(2013) Faulín Fajardo, Javier
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
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
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
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
Simulation-optimization in logistics, transportation, and SCM
(MDPI, 2021) Juan, Ángel A.; Rabe, Markus; Goldsman, David; Faulín Fajardo, Javier; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Institute of Smart Cities - ISC
This is a reprint of articles from the Special Issue published online in the open access journal Algorithms (ISSN 1999-4893) (available at: https://www.mdpi.com/journal/algorithms/special issues/Simulation Optimization). This book provides a selected collection of recent works in the growing area of simulation-optimization methods applied to transportation, logistics, and supply chain networks. Many of the authors that contribute to the book are internationally recognized experts in the field, as well as frequent speakers at the prestigious Winter Simulation Conference, where some of the Guest Editors organize an annual track on logistics, transportation and supply chains. Inside this track, it is usual to find several sessions on the concept of simheuristics, a special type of simulation optimization that combines metaheuristics with simulation to deal with complex and large-scale optimization problems under uncertainty conditions. The chapters in the book cover a wide area of logistics and transportation applications, from bike-sharing systems to container terminals, parcel locker systems, or e-commerce applications.