The mixed capacitated general routing problem with turn penalties

Bräysy, Olli; Martínez, Eulalia; Nagata, Yuichi; Soler, David

doi:10.1016/j.eswa.2011.04.092

Cited by 19 publications

(19 citation statements)

References 20 publications

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“…This set has been recently used by Bräysy et al (2011) as a benchmark set to test the efficiency of a memetic algorithm for a capacitated vehicle routing problem.…”

Section: Other Resultsmentioning

confidence: 99%

“…It is worth commenting here that the idea of solving a single-vehicle routing problem by transforming it into an ATSP through an AGTSP has been recently generalized to solve different hard multivehicle routing problems, as we can see through the papers by Soler et al (2009), Baldacci et al (2010, Bräysy et al (2011), and Micó and Soler (2011).…”

Section: Given a Directed Graph G = (V A) With Nonnegative Costs Assmentioning

confidence: 99%

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A new genetic algorithm for the asymmetric traveling salesman problem

Nagata

Soler

2012

Expert Systems with Applications

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“…This set has been recently used by Bräysy et al (2011) as a benchmark set to test the efficiency of a memetic algorithm for a capacitated vehicle routing problem.…”

Section: Other Resultsmentioning

confidence: 99%

Section: Given a Directed Graph G = (V A) With Nonnegative Costs Assmentioning

confidence: 99%

A new genetic algorithm for the asymmetric traveling salesman problem

Nagata

Soler

2012

Expert Systems with Applications

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“…Downloaded 12/15/14 to 132.236.27.111. Redistribution subject to SIAM license or copyright; see http://www.siam.org/journals/ojsa.php Some tools support detailed street routing constraints, like U-turns, turning penalties (Bräysy et al [6]), street side management (e.g., meandering/zigzagging) (Irnich [38]), dynamic usability of roads (e.g., due to congestion or accidents), and hazmat (hazardous material) routing constraining the feasible path options (Akgün et al [1]). …”

Section: Plan Related Constraintsmentioning

confidence: 99%

Chapter 12: Software Tools and Emerging Technologies for Vehicle Routing and Intermodal Transportation

Bräysy¹,

Hasle²

2014

Vehicle Routing

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Vehicle routing is a central task in a large number of private and public corporations (see, e.g., Golden, Raghavan, and Wasil [30]). Tours have to be planned in very diverse sectors of the economy, not only in the logistics and transport business but in virtually all industrial sectors producing physical goods. Variants of the vehicle routing problem manifest in a remarkably wide range of commercial and non-commercial enterprises: from waste/refuse collection to retail distribution; from construction material delivery planning to postal and express delivery routing; from inbound manufacturing component transportation to finished car distribution; from in-home primary health care service to hospital operations; from transportation network optimization to third Party Logistics (3PL) operation scheduling; and from bulk collection and delivery planning to passenger transportation routing. Hence, vehicle routing is key to logistics efficiency in industry, the public sector, and society in general. The high complexity of the vehicle routing problem renders purely human planning inadequate for most applications. Typically, humanmade plans have a large potential for improvement. Also, non-assisted planning occupies valuable human resources. Therefore, high-quality software tools for decision support in vehicle routing are crucial to effective and efficient planning in many sectors of society.Vehicle Routing Problems (VRPs) in their many guises have been the subject of intensive study for more than half a century now (see Laporte [41]). These research efforts have led to the development of a variety of models and solution algorithms and the publication of thousands of scientific papers. Our ability to solve VRPs has increased tremendously over the past half century due to a combination of better VRP methods and the general performance improvement of computers. These results have, together with the progress of key enabling technologies, led to the emergence of numerous software companies worldwide, selling commercial vehicle routing software tools and accompanying services (see Hallamäki et al. [32], Drexl [13], and Partyka and Hall [50]). Among the 351 Downloaded 12/15/14 to 132.236.27.111. Redistribution subject to SIAM license or copyright; see http://www.siam.org/journals/ojsa.php

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“…Bautista and Pereira showed that when the restricted turns are numerous, they should be considered during the construction phase. Later, Soler et al and Bräysy et al studied the mixed general routing problem with turn penalties. Lacomme et al adapted Dijkstra's algorithm to compute the shortest paths between all pairs of edges.…”

Section: Related Workmentioning

confidence: 99%

“…Specifically, for a given priority class p that is not the lowest, the total number of times a vehicle enters a link at class p or higher must be greater than or equal to the number of times it leaves for the same class. The flow conservation constraints (6) ensure that each vehicle entering link j is coming from an adjacent link i and leaving through another adjacent link m. Constraints (7) ensure that all the required links are serviced during the corresponding priority class. Constraints (8) and (9) ensure that each vehicle starts at the depot and exits the network when its route is completed.…”

Section: Mathematical Formulationmentioning

confidence: 99%

Solving the large‐scale min–max K‐rural postman problem for snow plowing

et al. 2017

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International audienceThis article studies the snow plow routing problem, which is a modified version of the min–max problem with k-vehicles for arc routing on a mixed graph with hierarchy. Each arc or edge is given a priority and instead of minimizing the overall finishing time, we minimize the latest finishing time for each priority class. We consider turn restrictions, route balancing, and variable vehicle speeds in a real large-scale network. To solve the problem, we present a graph transformation from a directed rural postman problem with turn penalties to an asymmetric traveling salesman problem. We then make the following modifications to the metaheuristics to better handle the constraints: development of new neighborhood operators, several applications of the same destruction operators before repair of the solution, and a dynamic arc-grouping procedure when links are removed or inserted. We tested our methodology on three real networks with 1,626 to 2,146 street segments and 613 to 723 intersections. The results show that our approach can improve the solution, and the grouping procedure is helpful. The results also show that some operators perform better than others; the network topology seems to explain these variations. Finally, we validated our methodology by comparing to some routes planned in the past and to some routes obtained from a commercial solver

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The mixed capacitated general routing problem with turn penalties

Abstract: suggested. The experimental results show that the average deviation of the suggested solution method is less than 0.05 per cent with respect to optimum.

Cited by 19 publications

References 20 publications

A new genetic algorithm for the asymmetric traveling salesman problem

A new genetic algorithm for the asymmetric traveling salesman problem

Chapter 12: Software Tools and Emerging Technologies for Vehicle Routing and Intermodal Transportation

Solving the large‐scale min–max K‐rural postman problem for snow plowing

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