CREATING BALANCED AND CONNECTED CLUSTERS TO IMPROVE SERVICE DELIVERY ROUTES IN LOGISTICS PLANNING

Journal of Systems Science and Systems Engineering

Volumn 19, Issue 4, 2010, Pages 453-480

  Cao, Buyang ^a   Glover, Fred ^b  

^a ESRI   (United States)

^b OptTek Systems Inc   (United States)

Author keywords

Clustering; K means; logistics; routing; Thiessen polygon

Indexed keywords

CLUSTERING; COMPUTATIONAL RESULTS; K-MEANS; LOGISTICS PLANNING; MULTIPLE CRITERIA; PERSONAL SERVICES; ROUTING; SERVICE DELIVERY; THIESSEN POLYGON;

CUSTOMER SATISFACTION;

SALES;

EID: 78650417028     PISSN: 10043756     EISSN: None     Source Type: Journal    
DOI: 10.1007/s11518-010-5150-x     Document Type: Article

References (15)

1. Barreto, S., Ferreira, C., Paixao, J. & Santos, B. S. (2007). Using clustering analysis in a capacitated location-routing problem. European Journal of Operational Research, 179: 968-977.
2. Blakeley, F., Bozkaya, B., Cao, B. & Hall, W. (2003). Optimizing periodic maintenance operations for Schindler Elevator Corporation. Interfaces, 33: 67-79.
3. Braysy, O. & Gendreau, M. (2005). Vehicle routing problems with time windows, part I: route construction and local search algorithms. Transportation Science, 39: 104-118.
4. Braysy, O. & Gendreau, M. (2005). Vehicle routing problems with time windows, part II: metaheuristics. Transportation Science, 39: 119-139.
5. Dondo, R. & Cerda, J. (2007). A cluster-based optimization approach for the multi-depot heterogeneous fleet vehicle routing problem with time windows. European Journal of Operational Research, 176: 1478-1507.
6. Estivill-Castro, V. & Lee, I. (2001). Fast spatial clustering with different metrics and in the presence of obstacles. In: GIS'01, 142-147, November 9-10, 2001.
7. Fan, B. (2009). A hybrid spatial data clustering method for site selection: the data driven approach of GIS mining. Experts Systems with Applications, 36: 3923-3936.
8. Hruschka, H. & Natter, M. (1999). Comparing performance of feedforward neural nets and K-means for cluster-based market segmentation. European Journal of Operational Research, 114: 346-355.
9. Huff, D. L. (1963). A probabilistic analysis of shopping center trade areas. Land Economics, 39: 81-90.
10. Humair, S. & Willems, S. P. (2006). Optimizing strategic safety stock placement in supply chains with clusters of commonality. Operations Research, 54: 725-742.
11. Karypis, G. & Kumar, V. (1998). A fast and high quality multilevel scheme for partitioning irregular graphs. SIAM Journal of Scientific Computing, 20: 359-392.
12. th International Conference on Computational Science and Applications, IEEE Computer Society, 480-485.
13. MacQueen, J. B. (1967). Some methods for classification and analysis of multivariate observations. In: Proceedings of 5-th Berkeley Symposium on Mathematical Statistics and Probability, 1: 281-297, Berkeley, University of California Press.
14. Strehl, A. & Ghosh, J. (2002). Relationship-based clustering and visualization for high-dimensional data mining. INFORMS Journal on Computing, 1-23.
15. Zhang, B., Yin, W. J., Xie, M. & Dong, J. (2007). Geo-spatial clustering with non-spatial attributes and geographic non-overlapping constraint: a penalized spatial distance measure. In: Proceeding of PAKKD'07, 1072-1079, Springer-Verlag Berlin Heidelberg.