A Multicriteria Analysis for the Green VRP: A Case Discussion for the Distribution Problem of a Spanish Retailer

[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)Sawik, B.; Faulin, J.; Pérez Bernabeu, E. (2017). A Multicriteria Analysis for the Green VRP: A Case Discussion for the Distribution Problem of a Spanish Retailer. Transportation Research Procedia. 22:305-313. https://doi.org/10.1016/j.trpro.2017.03.037S3053132

Analyzing the benefits of an integrated mobility system using a matheuristic routing algorithm

In many Western countries, governments are currently implementing an innovative demand-driven mo- bility policy. Providers of collective door-to-door transport, called dial-a-ride services , are increasingly in- voked to replace unprofitable public transport in rural areas. This requires an integrated mobility system in which a user’s trip may consist of a combination of dial-a-ride services and regular public transport. In order to optimally integrate both systems from an operational point of view, dial-a-ride providers need to solve a challenging routing problem. Their flexible vehicle routes should be synchronized to the timetables of the remaining public transport services, while the optimal selection of the users’ transfer terminals depends on the actual structure of the dial-a-ride routes. This paper introduces a routing al- gorithm and integrated scheduling procedure to enforce this synchronization for problems of a realistic scale, enabling the design and operational implementation of an integrated mobility system. Experiments, performed on a new artificial benchmark data set with realistic characteristics, clearly indicate that from the perspective of the dial-a-ride providers, considerable operational benefits can be obtained by inte- grating public transport into their services. The resulting distance savings for the dial-a-ride vehicles are shown to depend on the operational characteristics of the system, the geographical distribution of the demand, and the ability to flexibly assign transfer terminals to user requests. Furthermore, the proposed algorithm is also very efficient in solving related problems in passenger and freight transport.Acknowledgements Yves Molenbruch is a postdoctoral researcher funded by the Re- search Foundation Flanders (FWO-1202719N). Kris Braekers is supported by the Special Research Fund (BOF) of Hasselt University (BOF20TT03). Patrick Hirsch is supported by the Österreichische Nationalbank (OeNB), Austria (project number 17703). This research is also supported by the Strategic Basic Re- search project Data-driven logistics ( FWO-S007318N ), funded by the Research Foundation Flanders (FWO). The computational resources and services used in this work were provided by the VSC (Flemish Supercomputer Center), funded by the Research Foundation Flanders (FWO) and the Flemish Government