A Grid-Based Genetic Approach to Solving the Vehicle Routing Problem with Time Windows
This paper describes one grid-based genetic algorithm approach to solve the vehicle routing problem with time windows in one experimental cluster MiniGrid. Clusters used in this approach are located in two Mexican cities (Cuernavaca and Jiutepec, Morelos) securely communicating with each other since...
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doaj-89bfa8e119eb42c4b7f10c9b687a88df2020-11-25T01:55:17ZengMDPI AGApplied Sciences2076-34172019-09-01918365610.3390/app9183656app9183656A Grid-Based Genetic Approach to Solving the Vehicle Routing Problem with Time WindowsMarco Antonio Cruz-Chávez0Abelardo Rodríguez-León1Rafael Rivera-López2Martín H. Cruz-Rosales3Research Center in Engineering and Applied Sciences, Autonomous University of Morelos State (UAEM), Avenida Universidad 1001 Colonia Chamilpa, C.P. 62209 Cuernavaca, Morelos, MexicoDepartment of Systems and Computing, México National Technological/I.T. Veracruz, Calzada Miguel Ángel de Quevedo 2779, C.P. 91860 Veracruz, MexicoDepartment of Systems and Computing, México National Technological/I.T. Veracruz, Calzada Miguel Ángel de Quevedo 2779, C.P. 91860 Veracruz, MexicoFaculty of Accounting, Administration & Informatics, UAEM, Avenida Universidad 1001 Colonia Chamilpa, C.P. 62209 Cuernavaca, Morelos, MexicoThis paper describes one grid-based genetic algorithm approach to solve the vehicle routing problem with time windows in one experimental cluster MiniGrid. Clusters used in this approach are located in two Mexican cities (Cuernavaca and Jiutepec, Morelos) securely communicating with each other since they are configured as one virtual private network, and its use as a single set of processors instead of isolated groups allows one to increase the computing power to solve complex tasks. The genetic algorithm splits the population of candidate solutions in several segments, which are simultaneously mutated in each process generated by the MiniGrid. These mutated segments are used to build a new population combining the results produced by each process. In this paper, the MiniGrid configuration scheme is described, and both the communication latency and the speedup behavior are discussed. Experimental results show one information exchange reduction through the MiniGrid clusters as well as an improved behavior of the evolutionary algorithm. A statistical analysis of these results suggests that our approach is better as a combinatorial optimization procedure as compared with other methods.https://www.mdpi.com/2076-3417/9/18/3656networksgenetic algorithmsvirtual private networksuper-linear speeduplatency |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Marco Antonio Cruz-Chávez Abelardo Rodríguez-León Rafael Rivera-López Martín H. Cruz-Rosales |
spellingShingle |
Marco Antonio Cruz-Chávez Abelardo Rodríguez-León Rafael Rivera-López Martín H. Cruz-Rosales A Grid-Based Genetic Approach to Solving the Vehicle Routing Problem with Time Windows Applied Sciences networks genetic algorithms virtual private network super-linear speedup latency |
author_facet |
Marco Antonio Cruz-Chávez Abelardo Rodríguez-León Rafael Rivera-López Martín H. Cruz-Rosales |
author_sort |
Marco Antonio Cruz-Chávez |
title |
A Grid-Based Genetic Approach to Solving the Vehicle Routing Problem with Time Windows |
title_short |
A Grid-Based Genetic Approach to Solving the Vehicle Routing Problem with Time Windows |
title_full |
A Grid-Based Genetic Approach to Solving the Vehicle Routing Problem with Time Windows |
title_fullStr |
A Grid-Based Genetic Approach to Solving the Vehicle Routing Problem with Time Windows |
title_full_unstemmed |
A Grid-Based Genetic Approach to Solving the Vehicle Routing Problem with Time Windows |
title_sort |
grid-based genetic approach to solving the vehicle routing problem with time windows |
publisher |
MDPI AG |
series |
Applied Sciences |
issn |
2076-3417 |
publishDate |
2019-09-01 |
description |
This paper describes one grid-based genetic algorithm approach to solve the vehicle routing problem with time windows in one experimental cluster MiniGrid. Clusters used in this approach are located in two Mexican cities (Cuernavaca and Jiutepec, Morelos) securely communicating with each other since they are configured as one virtual private network, and its use as a single set of processors instead of isolated groups allows one to increase the computing power to solve complex tasks. The genetic algorithm splits the population of candidate solutions in several segments, which are simultaneously mutated in each process generated by the MiniGrid. These mutated segments are used to build a new population combining the results produced by each process. In this paper, the MiniGrid configuration scheme is described, and both the communication latency and the speedup behavior are discussed. Experimental results show one information exchange reduction through the MiniGrid clusters as well as an improved behavior of the evolutionary algorithm. A statistical analysis of these results suggests that our approach is better as a combinatorial optimization procedure as compared with other methods. |
topic |
networks genetic algorithms virtual private network super-linear speedup latency |
url |
https://www.mdpi.com/2076-3417/9/18/3656 |
work_keys_str_mv |
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