Selected Multi-Criteria Green Vehicle Routing Problems
Applications of Management Science
ISBN: 978-1-78714-283-1, eISBN: 978-1-78714-282-4
ISSN: 0276-8976
Publication date: 5 May 2017
Abstract
The purpose of this chapter is to optimize multi-criteria formulation for green vehicle routing problems by mixed integer programming. This research is about the road freight transportation of a Spanish company of groceries. This company has more power in the north of Spain and hence it was founded there. The data used for the computational experiments are focused in the northern region of Spain. The data have been used to decide the best route in order to obtain a minimization of costs for the company. The problem focused on the distance traveled and the altitude difference; by studying these parameters, the best solution of route transportation has been made. The software used to solve this model is CPLEX solver with AMPL programming language. This has been helpful to obtain the results for the research and some conclusions have been obtained from them.
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Acknowledgements
Acknowledgments
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). The authors are grateful to anonymous reviewers for their comments. The authors would like to express their thanks to Erasmus student Rosario Villar from Public University of Navarre at Pamplona, Spain, who during her stay at AGH University of Science & Technology at Krakow, Poland, helped in preparing some tables, graphs, and some analyses of results presented in this chapter.
Citation
Sawik, B., Faulin, J. and Pérez-Bernabeu, E. (2017), "Selected Multi-Criteria Green Vehicle Routing Problems", Applications of Management Science (Applications of Management Science, Vol. 18), Emerald Publishing Limited, pp. 57-83. https://doi.org/10.1108/S0276-897620170000018003
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