BUSCADOR RECOLECTA

[EN] 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 planning delivery 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., This work has been partially supported by the National Research Center (NCN), Poland (DEC2013/11/B/ST8/04458),
by AGH, and by the Spanish Ministry of Economy and Competitiveness (TRA2013-48180-
C3-P and TRA2015-71883-REDT), and the Ibero-American Program for Science and Technology for Development
(CYTED2014-515RT0489). Likewise, we want to acknowledge the support received by the CAN Foundation in
Navarre, Spain (Grants CAN2014-3758 and CAN2015-70473). The authors are grateful to anonymous reviewers for
their comments.

[EN] Since its appearance in the 1990s, horizontal collaboration (HC) practices have revealed themselves as catalyzers for optimizing the distribution of goods in freight transport logistics. After introducing the main concepts related to HC, this paper offers a literature review on the topic and provides a classification of best practices in HC. Then, the paper analyses the main benefits and optimization challenges associated with the use of HC at the strategic, tactical, and operational levels. Emerging trends such as the concept of ` green' or environmentally- friendly HC in freight transport logistics are also introduced. Finally, the paper discusses the need of using hybrid optimization methods, such as simheuristics and learnheuristics, in solving some of the previously identified challenges in real- life scenarios dominated by uncertainty and dynamic conditions., This work has been partially supported by the Spanish Ministry of Economy and Competitiveness & FEDER (TRA2013-48180-C3-P, TRA2015-71883-REDT), The Erasmus+ program (2016-1-ES01-KA108-023465), the Ibero American Program of Science and Technology for Development (CYTED2014-515RT-0489), the CAN Foundation (CAN2014-3758, CAN2015-70473), and the Spanish Ministry of Education (FPU-14/00024).

[EN] This research presents the group of green vehicle routing problems with environmental costs translated into money versus production of noise, pollution and fuel consumption. This research is focused on multi-objective green logistics optimization. Optimality criteria are environmental costs: minimization of amount of money paid as externality cost for noise, pollution and costs of fuel versus minimization of noise, pollution and fuel consumption themselves. Some mixed integer programming formulations of multi-criteria vehicle routing problems have been considered. Mathematical models were formulated under assumption of existence of asymmetric distance-based costs and use of homogeneous fleet. The exact solution methods are applied for finding optimal solutions. The software used to solve these models is the CPLEX solver with AMPL programming language. The researchers were able to use real data from a Spanish company of groceries. Problems deal with green logistics for routes crossing the Spanish regions of Navarre, Basque Country and La Rioja. Analyses of obtained results could help logistics managers to lead the initiative in area of green logistics by saving money paid for environmental costs as well as direct cost of fuel and minimization of pollution and noise., This work has been partially supported by the National Research Center (NCN), Poland (DEC-2013/11/B/ST8/04458), by AGH, and by the Spanish Ministry of Economy and Competitiveness (TRA2013-48180-C3-P and TRA2015-71883-REDT), and the Ibero-American Program for Science and Technology for Development (CYTED2014-515RT0489). Likewise, we want to acknowledge the support received by the CAN Foundation in Navarre, Spain (Grants CAN2014-3758 and CAN2015-70473)

Incluye correcciones [Energies 2016, 9(7), 546; doi:10.3390/en9070546], Current logistics and transportation (L&T) systems include heterogeneous fleets consisting of common internal combustion engine vehicles as well as other types of vehicles using “green” technologies, e.g., plug-in hybrid electric vehicles and electric vehicles (EVs). However, the incorporation of EVs in L&T activities also raise some additional challenges from the strategic, planning, and operational perspectives. For instance, smart cities are required to provide recharge stations for electric-based vehicles, meaning that investment decisions need to be made about the number, location, and capacity of these stations. Similarly, the limited driving-range capabilities of EVs, which are restricted by the amount of electricity stored in their batteries, impose non-trivial additional constraints when designing efficient distribution routes. Accordingly, this paper identifies and reviews several open research challenges related to the introduction of EVs in L&T activities, including: (a) environmental-related issues; and (b) strategic, planning and operational issues associated with “standard” EVs and with hydrogen-based EVs. The paper also analyzes how the introduction of EVs in L&T systems generates new variants of the well-known Vehicle Routing Problem, one of the most studied optimization problems in the L&T field, and proposes the use of metaheuristics and simheuristics as the most efficient way to deal with these complex optimization problems., This work has been partially supported by the Spanish Ministry of Economy and Competitiveness (TRA2013-48180-C3-P and TRA2015-71883-REDT), FEDER, and the CYTED Program (CYTED2014-515RT0489). Likewise, we want to acknowledge the support received by the Catalan Government (2014-CTP-00001) and the CAN Foundation (CAN2014-3758 and CAN2015-70473).

Many combinatorial optimization problems (COPs) encountered in real-world logistics, transportation,
production, healthcare, financial, telecommunication, and computing applications are NP-hard in nature.
These real-life COPs are frequently characterized by their large-scale sizes and the need for obtaining
high-quality solutions in short computing times, thus requiring the use of metaheuristic algorithms. Metaheuristics
benefit from different random-search and parallelization paradigms, but they frequently assume
that the problem inputs, the underlying objective function, and the set of optimization constraints
are deterministic. However, uncertainty is all around us, which often makes deterministic models oversimplified
versions of real-life systems. After completing an extensive review of related work, this paper
describes a general methodology that allows for extending metaheuristics through simulation to solve
stochastic COPs. ‘Simheuristics’ allow modelers for dealing with real-life uncertainty in a natural way by
integrating simulation (in any of its variants) into a metaheuristic-driven framework. These optimization-driven
algorithms rely on the fact that efficient metaheuristics already exist for the deterministic version
of the corresponding COP. Simheuristics also facilitate the introduction of risk and/or reliability analysis
criteria during the assessment of alternative high-quality solutions to stochastic COPs. Several examples
of applications in different fields illustrate the potential of the proposed methodology., This work has been partially supported by the Spanish Ministry
of Economy and Competitiveness (grant TRA2013-48180-C3-P),
FEDER, and the Ibero-American Programme for Science and
Technology for Development (CYTED2014-515RT0489). Likewise
we want to acknowledge the support received by the Department
of Universities, Research & Information Society of the Catalan
Government (Grant 2014-CTP-00001) and the CAN Foundation
(Navarre, Spain) (Grant 3CAN2014-3758).

Ponencia presentada al 19th EURO Working Group on Transportation Meeting, EWGT2016, 5-7 septiembre de 2016, Estambul (Turquía), This research presents the group of green vehicle routing problems with environmental costs translated into money versus production of noise, pollution and fuel consumption. This research is focused on multi-objective green logistics optimization. Optimality criteria are environmental costs: minimization of amount of money paid as externality cost for noise, pollution and costs of fuel versus minimization of noise, pollution and fuel consumption themselves. Some mixed integer programming formulations of multi-criteria vehicle routing problems have been considered. Mathematical models were formulated under assumption of existence of asymmetric distance-based costs and use of homogeneous fleet. The exact solution methods are applied for finding optimal solutions. The software used to solve these models is the CPLEX solver with AMPL programming language. The researchers were able to use real data from a Spanish company of groceries. Problems deal with green logistics for routes crossing the Spanish regions of Navarre, Basque Country and La Rioja. Analyses of obtained results could help logistics managers to lead the initiative in area of green logistics by saving money paid for environmental costs as well as direct cost of fuel and minimization of pollution and noise., This work has been partially supported by the National Research Center (NCN), Poland
(DEC-2013/11/B/ST8/04458), by AGH, and by the Spanish Ministry of Economy and
Competitiveness (TRA2013-48180-C3-P and TRA2015-71883-REDT), and the Ibero-American Program for Science and Technology for Development (CYTED2014-515RT0489). Likewise,
we want to acknowledge the support received by the CAN Foundation in Navarre, Spain (Grants
CAN2014-3758 and CAN2015-70473).

Ponencia presentada al 19th EURO Working Group on Transportation Meeting, EWGT2016, 5-7 septiembre de 2016, Estambul (Turquía), Facilities location is a strategic decision which has to be carefully considered because it could involve the failure or success of a
business. For that reason, anything that helps decision makers to facilitate their location decision processes is of their utmost
interest. The aim of this paper is, therefore, providing a methodology that could be useful for the decision makers by giving them
not only an optimal point but also a whole region where they can focus on their attention. Knowing that biofuels are settling as a
new alternative energy source which has been spreading around the world to reduce greenhouse gas emissions and oil
dependence, this methodology is tested in the real case of locating a biorefinery in Navarre, Spain. Moreover, A Mixed Integer
Linear Programming (MILP) model has been developed to generate optimal region vertices as well as some other supply chain
characteristics, including, among others, which crops are going to be harvested, when they are going to be collected, and their
storage levels. Additionally, two criteria were implemented in MILP model to create two optimal regions: one considering an
economic criterion and other one minimizing environmental impact. As a result, two regions were drawn in the Navarrese
territory that point out where a biorefinery should be located and how the supply chain should be designed., This work has been partially supported by the Government of Navarre (Biorefinery Navarra project IIM14196.RI1) the Spanish Ministry of Economy and Competitiveness (TRA2013-48180-C3-P and TRA2015-71883-REDT), and the Ibero-American Program for Science and Technology for Development (CYTED2014-515RT0489). Likewise, we want to acknowledge the support received by the CAN Foundation in Navarre, Spain (Grant CAN2015-70473).

Trabajo presentado a la 13th Conference on Transport Engineering, CIT 2018. Gijón, 6-8 de junio de 2018., The city of Pamplona, in Spain, is currently experiencing several changes regarding sustainable mobility such as pedestrianization of some streets in the city center, and access control to the Old Town for motor vehicles through the use of automatic number-plate recognition. However, some groups including local neighbors and businesses are raising complaints as they are being affected by these measures. This is also the case for couriers and logistics companies which have now to comply with new regulations regarding delivery routes throughout the Old Town. This paper will present a comprehensive study of the situation that is being carried out, and in which social perceptions and freight traffic patterns in the Old Town of Pamplona are analyzed to understand how urban freight distribution could be improved in the area. For this purpose, we make use of a survey-based research to the stakeholders, i.e. pedestrians, logistics companies, retailers, and authorities of Pamplona. Results highlight pollution derived from transportation, lack of parking spaces as well as invasion of public spaces in the city center as the key issues for improving freight transportation in the Old Town. Finally, placing a distribution center in the Old Town and the promotion of the cycle-logistics are considered as the future of the urban distribution in Pamplona., This work has been partially supported by the Spanish Ministry of Economy and Competitiveness (TRA2013-48180-C3-P and TRA2015-71883-REDT), FEDER, and the Ibero-American Program for Science and Technology for Development (CYTED2014-515RT0489). Moreover, we appreciate the financial support of the Erasmus+ Program (2016-1-ES01-KA108-023465) and the CAN Foundation in Navarre, Spain (Grant CAN2017-6101). Likewise, we want to acknowledge the financial support received by Spanish Ministry of Education (Grant FPU 2014-0024).

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., This work has been partially supported by the Government of Navarre (Biorefinery Navarra project IIM14196.RI1), the Spanish Ministry of Economy and Competitiveness (TRA2013-48180-C3-P and TRA2015-71883-REDT), and the Ibero-American Program for Science and Technology for Development (CYTED2014-515RT0489). Likewise, we want to acknowledge the support received by the CAN Foundation in Navarre, Spain (Grant CAN2017-6101).

Despite its negative impacts, freight transportation is a primary component of all supply chains. Decision makers have considered diverse strategies, such as Horizontal Collaboration (HC) and the usage of alternative types of vehicles, to reduce overall cost and the related environmental and social impacts. This paper assesses the implementation of an electric fleet of vehicles in urban goods distribution under HC strategy between carriers. A biased randomisation based algorithm is used to solve the problem with a multi-objective function to explore the relationships between both delivery and environmental costs. Real data from the city of Bogota, Colombia are used to validate this approach. Experiments with different costs and demands projections are performed to analyse short- and medium-term impacts related to the usage of electric vehicles in collaborative networks. Results show that the optimal selection of vehicle types depends considerably on the time horizon evaluation and demand variation., This work has been partially supported by the Spanish Ministry of Economy and Competitiveness (TRA2013-48180-C3-P and TRA2015-71883-REDT) and the Ibero-American Program for Science and Technology for Development (CYTED2014-515RT0489). Likewise, we want to acknowledge the support received by the Special Patrimonial Fund from Universidad de La Sabana (Colombia) and the doctoral grant from the UOC-Open University of Catalonia (Spain).