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South African Journal of Industrial Engineering

versão On-line ISSN 1012-277X

S. Afr. J. Ind. Eng. vol.21 no.2 Pretoria  2010

 

GENERAL ARTICLE

 

Activity-based costing for vehicle routing problems

 

 

A.J. MoolmanI; K.KoenII; J. van der WesthuizenIII

IDepartment of Industrial Engineering, University of Pretoria, South Africa alwyn@e-Logics.co.za
IIDepartment of Business Management, University of Pretoria, South Africa kkoen@clover.co.za
IIIe-Logics Pty Ltd, South Africa johann@e-Logics.co.za

 

 


ABSTRACT

Activity-based costing (ABC) is a costing model that identifies activity costs in an organisation. It assigns the cost of activity resources to generate the actual cost of products in order to eliminateunprofitable products and to lowerthe prices of overpriced ones. The vehicle routing problem (VRP) is a combinatorial optimisation and nonlinear programming problem that seeks to service a number of customers with a fleet of vehicles in a cost-effective manner. In this article we propose a new approach to determine costing for vehicle routing type problems. The methodology incorporates the predictive sharing of a resource by clustering producers.


OPSOMMING

'Activity-based costing' (ABC) is 'n kostemodel wat die aktiwiteitskoste in 'n organisasie identifiseer. Dit allokeer die koste van die bronne sodat die ware koste van die vervaardiging en dienste van die produk bereken kan word om winsgewendheid te bepaal. Die 'vehicle routing problem' (VRP) is 'n kombinatoriese optimisering en nie-lineêre programmeringsprobleem wat verskeie kliënte met 'n vloot voertuie in die mees koste-effektiewe manier bedien. Die artikel bespreek 'n nuwe metode om die kombinasie van probleme op te los. Die metode maak gebruik van groeperingsalgoritmes om meer akkurate voertuig deling te voorspel.


 

 

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REFERENCES

[1] Bianchi, L., Birattari, M., Manfrin, M., Mastrolilli, M., Paquete, L., Rossi-Doria, O., et al. (2004, March). Research on the Vehicle Routing Problem with Stochastic Demand. Technical Report IDSIA, IDSIA-07-04.         [ Links ]

[2] CAM-I. (2008) Overview of CAM-I. Consortium for Advanced Manufacturing-International: http://www.cam-i.org        [ Links ]

[3] Cengage, G. (2002). Activity-Based Costing. Encyclopedia of Small Business: http://www.enotes.com/small-business-encyclopedia/        [ Links ]

[4] Choi, E., Tcha, D. (2005). A column generation approach to the heterogeneous fleet vehicle routing problem. Computers & Operations Research, 34.         [ Links ]

[5] Dantzig, G., Ramser, J. (1959). The Truck Dispatching Problem. Management science, 6(1).         [ Links ]

[6] Dondo, R., Cerda, J. (2006). A cluster-based optimization approach for the multidepot heterogeneous fleet vehicle routing problem with time windows. European Journal of Operational Research , 176.         [ Links ]

[7] Ertöz, L., Steinbach, M., Kumar, V. (2003). Finding Clusters of Different Sizes, Shapes, and Densities in Noisy, High Dimensional Data. SIAM International Conference on Data Mining.         [ Links ]

[8] Ester, M., Kriegel, H., Sander, J., Xu, X. (1996). A Density Based Algorithm for Discovering Clusters in Large Spatial Database with Noise. Proceedings of 2nd International Conference on Knowledge Discovery and Data Mining (KDD-96). Portland, Oregon: Institute for Computer Science, University of Munich.         [ Links ]

[9] Estivill-Castro, V. (2002). Why so many clustering algorithms - A Position Paper. ACM SIGKDD Explorations Newsletter, 4(1, p65).         [ Links ]

[10] Golden, B., Raghavan, S., Wasil, E. (2008). The Vehicle Routing Problem, Latest Advances and New Challenges. Springer.         [ Links ]

[11] Han, J., Kamber, M. (2001). Data Mining Concepts and Techniques. San Francisco, CA: Morgan Kaufmann Publishers.         [ Links ]

[12] Kaplan, K., Robert, S., Bruns, W. (1987). Accounting and Management: A Field Study Perspective. Harvard Business School Press.         [ Links ]

[13] Laporte, G. (2009, August). Fifty Years of Vehicle Routing. Les Cahiers du GERAD(G-2009-43).         [ Links ]

[14] Moreira, A., Santos, M., Carneiro, S. (2008). Density based clustering algorithms. CiteSeerX: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.123.6125&rep= rep1&type=pdf        [ Links ]

[15] Park, H.-S., Lee, J.-S.,Jun, C.-H. (2006). A K-means-like algorithm for K-medoids clustering and its performance. Proceedings of ICCIE.         [ Links ]

[16] Peterson, J. (2002). Clustering Overview.CiteSeerX: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.136.4170&rep= rep1&type=pdf        [ Links ]

[17] Toth, P., Vigo, D. (2001). The Vehicle Routing Problem. Society for Industrial and Applied Mathematics Philadelphia, PA, USA.         [ Links ]

[18] Winston, W. (1994). Operations Research: Applications and Algorithms, Third Edition. California.         [ Links ]

[19] Yue, S., Li, P., Guo, J., Zhou, S. (2004). Using Greedy algorithm: DBSCAN revisited II. Journal of Zhejiang University-Science, 5(11). 172        [ Links ]

 

 

* Corresponding author.
1 The author was enrolled for a PhD (Industrial Engineering) degree in the Department of Industrial Engineering, University of Pretoria.
2 The author was enrolled for a Master Programme in Supply Chain Management (Business Management) certificate in the Department of Business Management, University of Pretoria.

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