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Journal of Applied Sciences
  Year: 2009 | Volume: 9 | Issue: 1 | Page No.: 79-87
DOI: 10.3923/jas.2009.79.87
 
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Hybrid Genetic Algorithm for Vehicle Routing and Scheduling Problem

K. Ghoseiri and S. F. Ghannadpour

Abstract:
This study aims to solve Vehicle Routing Problem with Time Windows (VRPTW), which has received considerable attention in recent years, using hybrid genetic algorithm. Vehicle Routing Problem with Time Windows is an extension of the well-known Vehicle Routing Problem (VRP) and involves a fleet of vehicles set-off from a depot to serve a number of customers at different geographic locations with various demands within specific time windows before returning to the depot eventually. To solve this problem, this study suggests a hybrid genetic algorithm combined with Push Forward Insertion Heuristic (PFIH) to make an initial solution and λ-interchange mechanism to neighborhood search and improving method. The proposed genetic algorithm uses an integer representation in which a string of customer identifiers represents the sequence of deliveries covered by each of the vehicles. Part of initial population is initialized using Push Forward Insertion Heuristic (PFIH) and part is initialized randomly. A λ-interchange mechanism interchanges the customers between routes and generates neighborhood solution. At the end, in order to prove the validity of the suggested model, fourteen instances of Solomon`s 56 benchmark problems-selected randomly- are solved and compared with the other meta-heuristic methods. The results indicate the good quality of the method.
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How to cite this article:

K. Ghoseiri and S. F. Ghannadpour, 2009. Hybrid Genetic Algorithm for Vehicle Routing and Scheduling Problem. Journal of Applied Sciences, 9: 79-87.

DOI: 10.3923/jas.2009.79.87

URL: https://scialert.net/abstract/?doi=jas.2009.79.87

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