A robust MILP-based approach to vehicle routing problems with uncertain demands

• Published in: Computer Aided Chemical Engineering Vol. 29; pp. 633 - 637
• Main Authors: Aguirre, A., Coccola, M., Zamarripa, M., Méndez, C., Espuña, A.
• Format: Book Chapter
• Language: English
• Published: 2011
• Subjects: MILP models; stochastic optimization; Vehicle routing problems; Vehicle routing problems; MILP models; stochastic optimization
• ISBN: 044453895X; 9780444538956
• ISSN: 1570-7946
• DOI: 10.1016/B978-0-444-53711-9.50127-9

The Vehicle Routing Problem with Stochastic Demands (VRPSD) has attracted the attention of the research community over the last decades by introducing the random behavior of the demand into the traditional routing problem. Many related works were focusing on providing suitable approaches of this large combinatorial problem for many different cases of uncertainly demand. Moreover, exact approaches that were developed up to now provide reliable results for specific demand values, e.g. using the highest demand value or the most expected value, but these solutions do not consider the concurrent effect of many possible scenarios into the objective function. So, the real necessity of more efficient and reliable approaches for this problem that provides optimal solutions for small and medium size cases in a reasonable time and also that response consistently to the random behavior of the demand has been clearly appeared in the last years (Novoa and Storer, 2009). In this work a robust MILP-based formulation for the VRPSD problem is developed. The main goal of this method is to find a reliable solution that provides an optimal result considering the occurrence of many possible scenarios in simultaneous.