Exact algorithms for different classes of vehicle routing problems

Roberti, Roberto

doi:10.1007/s10288-012-0206-z

Cited by 12 publications

(9 citation statements)

References 151 publications

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“…The authors evaluate the method on a set of 93 instances (Crainic et al, 2010;Perboli et al, 2011) for which 59 new best solutions are identified. In addition, a branch-and-cut method has been designed by Jepsen et al (2012) and a branch-and-price approach by Roberti (2012).…”

Section: Position In the Or Literaturementioning

confidence: 99%

Optimization of a city logistics transportation system with mixed passengers and goods

Masson

Trentini

Lehuédé

et al. 2017

EURO Journal on Transportation and Logistics

155

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Section: Position In the Or Literaturementioning

confidence: 99%

Optimization of a city logistics transportation system with mixed passengers and goods

Masson

Trentini

Lehuédé

et al. 2017

EURO Journal on Transportation and Logistics

155

View full text Add to dashboard Cite

show abstract

“…We use the truncated data to be able to compare our results to those given in Pisinger and Ropke (2005) and Demir et al (2012) as well as to the optimal solutions reported in Roberti (2012). For each instance we perform 10 runs.…”

Section: Computational Resultsmentioning

confidence: 98%

“…Note that most parameters (15 out of 19) have preserved their initial values tested. (2005) and Demir et al (2012), and with the optimal solutions reported in Roberti (2012). Table C.2 presents the new best-known solutions for the real-numbered R106, R107, R108, R210, and RC107 instances.…”

Section: Appendix B: Parameter Tuningmentioning

confidence: 97%

An Adaptive Large Neighborhood Search for an E-grocery Delivery Routing Problem

Emeç

Çatay

Bozkaya

2016

Computers & Operations Research

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“…In this table, " 2014), respectively. For all VRPTW instances with truncated distances except R208, the optimal solutions are available in Roberti (2012). The optimal distance for R208 is obtained from Röpke (2014).…”

Section: Resultsmentioning

confidence: 99%

An Ant Colony-Based Matheuristic Approach for Solving a Class of Vehicle Routing Problems

Yıldırım

Çatay

2015

Lecture Notes in Computer Science

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Abstract. We propose a matheuristic approach to solve several types of vehicle routing problems (VRP). In the VRP, a fleet of capacitated vehicles visits a set of customers exactly once to satisfy their demands while obeying problem specific characteristics and constraints such as homogeneous or heterogeneous fleet, customer service time windows, single or multiple depots. The proposed matheuristic is based on an ant colony optimization (ACO) algorithm which constructs good feasible solutions. The routes obtained in the ACO procedure are accumulated in a pool as columns which are then fed to an integer programming (IP) optimizer that solves the set-partitioning (-covering) formulation of the particular VRP. The (near-)optimal solution found by the solver is used to reinforce the pheromone trails in ACO. This feedback mechanism between the ACO and IP procedures helps the matheuristic better converge to high quality solutions. We test the performance of the proposed matheuristic on different VRP variants using well-known benchmark instances from the literature. Our computational experiments reveal competitive results: we report six new best solutions and meet the best-known solution in 120 instances out of 193. Keywords: Vehicle routing problem · Matheuristic · Ant colony optimization IntroductionThere is an increasing trend towards matheuristics in the recent literature as they incorporate relatively fast and effective solutions while preserving the solution quality. Matheuristics can do so by combining heuristics/metaheuristics with exact solution approaches. According to Boschetti et al. (2009), the interoperation of metaheuristics and mathematical programming techniques yields the matheuristics. The metaheuristic further exploits the features derived by the mathematical model of the problem. Bertazzi and Speranza (2011) simply define a matheuristic as any heuristic that uses mathematical programming in one of its solution steps such as solving sub-problems, solving parts of an instance, restricting the search space and exploring neighborhoods.

show abstract

Exact algorithms for different classes of vehicle routing problems

Cited by 12 publications

References 151 publications

Optimization of a city logistics transportation system with mixed passengers and goods

Optimization of a city logistics transportation system with mixed passengers and goods

An Adaptive Large Neighborhood Search for an E-grocery Delivery Routing Problem

An Ant Colony-Based Matheuristic Approach for Solving a Class of Vehicle Routing Problems

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