Considerations on Set Partitioning and Set Covering Models for Solving the 2E-CVRP in City Logistics

This chapter proposes a position viewpoint, discussion, and analysis of various aspects of solving 2E-CVRP problems via exact methods, more precisely the use of set partitioning formulations (and consequently set covering ones), as well as column generation to produce bounds and feed branch-and-prize approaches. After an overview of the main exact methods used to solve 2E-CVRP approaches, the author defines the main notions and variables to model the problem via set covering and set partitioning models. Then the paper presents two methods to generate bounds via column generation: the first is a decomposition approach in which first-echelon and second-echelon routes are generated separately, without any relation, and the second generate sets of linked first-echelon and second-echelon routes. The main implications and considerations of those methods are addressed. Finally, main issues regarding the suitability of exact methods for vehicle routing in city logistics are presented.

Author(s):  
Tsukasa Izuno ◽  
Tatsushi Nishi ◽  
Sisi Yin

The pickup and delivery crude oil transportation scheduling problem is to find an optimal assignment of requests to a fleet of tankers, sequence of visiting places, and loading and unloading volume of demand simultaneously in order to minimize the total cost with the capacity of the tankers. The problem can be formulated as a split pickup and delivery vehicle routing problem. We apply a column generation algorithm to solve the problem efficiently. In order to obtain a feasible solution by column generation, we propose an effective algorithm to generate a feasible solution satisfying the set partitioning constraints. Computational results demonstrate the effectiveness of the proposed method.


2009 ◽  
Vol 21 (1) ◽  
pp. 151-166 ◽  
Author(s):  
Giuseppe Lancia ◽  
Paolo Serafini

2019 ◽  
Vol 8 (2) ◽  
pp. 117-118
Author(s):  
Michael Schneider ◽  
Timo Gschwind ◽  
Daniele Vigo

2021 ◽  
Vol 12 (3) ◽  
pp. 293-304 ◽  
Author(s):  
Luis Fernando Galindres-Guancha ◽  
Eliana Toro-Ocampo ◽  
Ramón Gallego-Rendón

Vehicle routing problems (VRPs) have usually been studied with a single objective function defined by the distances associated with the routing of vehicles. The central problem is to design a set of routes to meet the demands of customers at minimum cost. However, in real life, it is necessary to take into account other objective functions, such as social functions, which consider, for example, the drivers' workload balance. This has led to growth in both the formulation of multiobjective models and exact and approximate solution techniques. In this article, to verify the quality of the results, first, a mathematical model is proposed that takes into account both economic and work balance objectives simultaneously and is solved using an exact method based on the decomposition approach. This method is used to compare the accuracy of the proposed approximate method in test cases of medium mathematical complexity. Second, an approximate method based on the Iterated Local Search (ILS) metaheuristic and Decomposition (ILS/D) is proposed to solve the biobjective Capacitated VRP (bi-CVRP) using test cases of medium and high mathematical complexity. Finally, the nondominated sorting genetic algorithm (NSGA-II) approximate method is implemented to compare both medium- and high-complexity test cases with a benchmark. The obtained results show that ILS/D is a promising technique for solving VRPs with a multiobjective approach.


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