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 simheuristic for routing electric vehicles with limited driving ranges and stochastic travel times(Institut d'Estadistica de Catalunya (Idescat), 2019) Reyes-Rubiano, Lorena Silvana; Ferone, Daniele; Juan Pérez, Ángel Alejandro; Faulín Fajardo, Javier; Institute of Smart Cities - ISC; Universidad Pública de Navarra / Nafarroako Unibertsitate PublikoaGreen transportation is becoming relevant in the context of smart cities, where the use of electric vehicles represents a promising strategy to support sustainability policies. However the use of electric vehicles shows some drawbacks as well, such as their limited driving-range capacity. This paper analyses a realistic vehicle routing problem in which both driving-range constraints and stochastic travel times are considered. Thus, the main goal is to minimize the expected time-based cost required to complete the freight distribution plan. In order to design reliable routing plans, a simheuristic algorithm is proposed. It combines Monte Carlo simulation with a multi-start metaheuristic, which also employs biased-randomization techniques. By including simulation, simheuristics extend the capabilities of metaheuristics to deal with stochastic problems. A series of computational experiments are performed to test our solving approach as well as to analyse the effect of uncertainty on the routing plans.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 Simheuristic algorithms for the sustainable freight transport problem(2019) Reyes-Rubiano, Lorena Silvana; Faulín Fajardo, Javier; Juan Pérez, Ángel Alejandro; Estadística, Informática y Matemáticas; Estatistika, Informatika eta Matematika; Universidad Pública de Navarra / Nafarroako Unibertsitate PublikoaThe sustainable freight transport entails the design of the distribution plans with the least negative impacts. On one hand, this distribution problem relies on deter-mining the routes to visit a set of customers, which can be geographically scattered. One the other hand, the operational constraints and the attributes involved in ur-ban transport need to be considered for designing the distribution plan. Distribution plans encompass not only the classical routing constraints but also a set of economic, social and environmental criteria implicated with transport sector. These attributes link social and industrial needs taking into account the triple bottom of objectives sustainability. Those attributes may be diÿcult to address because they can be pro-gressing in di˙erent directions. This thesis contributes to integrate these challenges by means of analysis of transport problems, and structured method developments for supporting the decision making process. To attain these challenges the following objectives have been proposed: • Identification of attributes and constrains for problems related to freight trans-port in smart cities, with especial focus on environmental, economic and social impacts. • Modeling of sustainability indicators in the vehicle routing problems with the purposes of producing greener transport in smart cities. • Design and implementation of hybrid algorithms combining metaheuristics with simulation to provide sustainable solutions. • Validation of the algorithms using realistic data and well-known solutions. The first objective is to provide a characterization in problems related to freight transport, considering a special focus on sustainability dimensions. Some measures to estimate the negative impacts caused by transport activities have been also in-cluded. In Chapter 1, the classical issues related to urban transport and the sus-tainability dimensions are presented. Afterwards, the Chapter 2 provides a general description of solving approaches for combinatorial optimization problems considering also an overview of the most common attributes and constraints related to the current sustainability initiatives. Then, the framework of biased randomized simheuristic algorithm is described to-gether with the most classical methods to solve rich vehicle routing problems. The proposed algorithms are well described across the chapters of this thesis. For the second objective of this dissertation, a formal description for routing problems with single depot and multi depot configuration. In Chapter 3 a sustainable multi-depot problem is defined and solved by a mixed integer programming and a variable neigh-borhood search framework. From Chapter 4 to Chapter 6, vehicles routing problem with electric is described assuming a single depot and stochastic variables. The third objective is a global one which will be addressed over the course of the whole dissertation. Easy to implement and competitive simheuristic algorithms are proposed to cope with stochastic problems. Particular attention is paid on the inclusion of sustainable criteria and consideration of current operational constraints from freight transport. The fourth objective is to implement and test the algorithms using benchmarks for deterministic and stochastic problems. The results show the sustainability influ-ence of the optimization criteria and the e˙ect of stochastic data on the performance of the solution approaches and solutions quality. Finally, this dissertation ends with some conclusions and comments on further research lines.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 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 Pricing and internalizing noise externalities in road freight transportation(Elsevier, 2017) Serrano Hernández, Adrián; Álvarez, Pablo; Lerga Valencia, Iosu; Reyes-Rubiano, Lorena Silvana; Faulín Fajardo, Javier; Institute of Smart Cities - ISCPeople living close to main roads may suffer from the nuisance of traffic and noise pollution. This paper assesses the effect of full routing cost in vehicle routing decisions by internalizing the external cost of noise. On a first step, noise externalities are economically assessed through a contingent valuation procedure. Secondly, a novel methodology is proposed to allocate the external costs to the road network links. Results show significant differences in routing planning depending on the approach: minimization of traditional internal cost versus minimization of full cost. These results encourage further research in pricing and methodologies to internalize externalities.Publication 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.