Person: Reyes-Rubiano, Lorena Silvana
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Reyes-Rubiano
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Lorena Silvana
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Estadística e Investigación Operativa
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0000-0003-0995-4049
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811229
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Publication 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 - ISCIn 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.Publication Open Access Exploration of a disrupted road network after a disaster with an online routing algorithm(Springer, 2020) Reyes-Rubiano, Lorena Silvana; Voegl, Jana; Rest, Klaus‑Dieter; Faulín Fajardo, Javier; Hirsch, Patrick; Institute of Smart Cities - ISC; Universidad Pública de Navarra / Nafarroako Unibertsitate PublikoaThis paper considers the problem of supporting immediate response operations after a disaster with information about the available road network to reach certain locations. We propose an online algorithm that aims to minimize the route length required by an unmanned aerial vehicle (UAV) to explore the road accessibility of potential victim locations. It is assumed that no information about disruptions in the road network is available at the start of the exploration. The online algorithm applies two movement and three orientation strategies. Additionally, a cutting strategy is used to restrict the search space after new information about the state of single roads is obtained. We consider a road and an aerial network for the movements of the UAV, since it is not necessary to follow the route of a road any longer, if it can be marked as disrupted. In extensive numerical studies with artificial and real-world test instances, it is evaluated for different disruption levels, which combinations of movement and orientation strategies perform best. Additionally, we propose different refuelling strategies for the UAV and present how they differ in the number of refuelling operations and the required additional route length. The results show that an efficient online algorithm can save valuable exploration time.Publication Open Access Curved beam through matrices associated with support conditions(2020) Gimena Ramos, Faustino; Gonzaga Vélez, Pedro; Valdenebro García, José Vicente; Goñi Garatea, Mikel; Reyes-Rubiano, Lorena Silvana; Ingeniería; IngeniaritzaPublication Open Access The sustainability dimensions in intelligent urban transportation: a paradigm for smart cities(MDPI, 2021) Reyes-Rubiano, Lorena Silvana; Serrano Hernández, Adrián; Montoya Torres, Jairo R.; Faulín Fajardo, Javier; Estatistika, Informatika eta Matematika; Institute of Smart Cities - ISC; Estadística, Informática y Matemáticas; Universidad Pública de Navarra / Nafarroako Unibertsitate PublikoaThe transportation sector has traditionally been considered essential for commercial activities, although nowadays, it presents clear negative impacts on the environment and can reduce social welfare. Thus, advanced optimization techniques are required to design sustainable routes with low logistic costs. Moreover, these negative impacts may be significantly increased as a consequence of the lack of synergy between the sustainability objectives. Correspondingly, the concept of transport optimization in smart cities is becoming popular in both the real world and academia when public decision making is lit by operations research models. In this paper, however, we argue that the level of urban smartness depends on its sustainability and on the level of information and communication technologies developed in the city. Therefore, the operations research models seek to achieve a higher threshold in the sustainable transport standards in smart cities. Thus, we present a generic definition of smart city, which includes the triple bottom line of sustainability, with the purpose of analyzing its effects on city performance. Finally, this work provides a consolidate study about urban freight transport problems, which show that sustainability is only one facet of the diamond of characteristics that depict a real smart city.