Variants of VRP to Optimize Logistics Management Problems

2012 ◽  
pp. 207-237 ◽  
Author(s):  
Claudia Gómez Santillán ◽  
Laura Cruz Reyes ◽  
María Lucila Morales Rodríguez ◽  
Juan Javier González Barbosa ◽  
Oscar Castillo López ◽  
...  
Keyword(s):  
Supply Chain ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Supply Chain Coordination ◽  
Real Life ◽  
Routing Problem ◽  
Transportation Management ◽  
Practical Applications ◽  
Operation Costs ◽  
Rich Vrp

The Vehicle Routing Problem (VRP) is a key to the efficient transportation management and supply-chain coordination. VRP research has often been too focused on idealized models with non-realistic assumptions for practical applications. Nowadays the evolution of methodologies allows that the classical problems could be used to solve VRP problems of real life. The evolution of methodologies allows the creation of variants of the VRP which were considered too difficult to handle by their variety of possible restrictions. A VRP problem that includes the addition of restrictions, which represent the variants in the problem, is called Rich VRP. This work presents an algorithm to optimize the transportation management. The authors are including a case of study which solves a real routing problem applied to the distribution of bottled products. The proposed algorithm shows a saving in quantity of vehicles and reduces the operation costs of the company.

scholarly journals The Robust Vehicle Routing Problem with Time Windows: Compact Formulation and Branch-Price-and-Cut Method

2019 ◽  
Vol 53 (4) ◽  
pp. 1043-1066 ◽  
Author(s):  
Pedro Munari ◽  
Alfredo Moreno ◽  
Jonathan De La Vega ◽  
Douglas Alem ◽  
Jacek Gondzio ◽  
...  
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Time Windows ◽  
Real Life ◽  
Set Partitioning ◽  
Branch And Cut ◽  
Small Scale ◽  
Routing Problem ◽  
Compact Formulation ◽  
Cut Method

We address the robust vehicle routing problem with time windows (RVRPTW) under customer demand and travel time uncertainties. As presented thus far in the literature, robust counterparts of standard formulations have challenged general-purpose optimization solvers and specialized branch-and-cut methods. Hence, optimal solutions have been reported for small-scale instances only. Additionally, although the most successful methods for solving many variants of vehicle routing problems are based on the column generation technique, the RVRPTW has never been addressed by this type of method. In this paper, we introduce a novel robust counterpart model based on the well-known budgeted uncertainty set, which has advantageous features in comparison with other formulations and presents better overall performance when solved by commercial solvers. This model results from incorporating dynamic programming recursive equations into a standard deterministic formulation and does not require the classical dualization scheme typically used in robust optimization. In addition, we propose a branch-price-and-cut method based on a set partitioning formulation of the problem, which relies on a robust resource-constrained elementary shortest path problem to generate routes that are robust regarding both vehicle capacity and customer time windows. Computational experiments using Solomon’s instances show that the proposed approach is effective and able to obtain robust solutions within a reasonable running time. The results of an extensive Monte Carlo simulation indicate the relevance of obtaining robust routes for a more reliable decision-making process in real-life settings.

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