A hybrid fuzzy-optimization approach to customer grouping-based logistics distribution operations

Applied Mathematical Modelling

Volumn 31, Issue 6, 2007, Pages 1048-1066

  Sheu, Jiuh Biing ^a  

^a NATIONAL CHIAO TUNG UNIVERSITY   (Taiwan)

Author keywords

En route goods delivery; Fuzzy clustering; Logistical distribution; Multi objective optimization; Pre route customer classification

Indexed keywords

ALGORITHMS; CUSTOMER SATISFACTION; FUZZY SETS; MANAGEMENT; OPTIMIZATION;

FUZZY CLUSTERING; LOGISTICAL DISTRIBUTION; MULTI-OBJECTIVE OPTIMIZATION; PRE-ROUTE CUSTOMER CLASSIFICATION;

OPERATIONS RESEARCH;

ALGORITHMS; CUSTOMER SATISFACTION; FUZZY SETS; MANAGEMENT; OPERATIONS RESEARCH; OPTIMIZATION;

EID: 33846157172     PISSN: 0307904X     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.apm.2006.03.024     Document Type: Article

References (46)

1. Golden B.L., and Assad A.A. Vehicle Routing: Methods and Studies (1988), North-Holland, Amsterdam
2. Bramel J., and Simchi-Levi D. The capacitated VRP with unequal demands. In: Bramel J., and Simchi-Levi D. (Eds). The Logic of Logistics (1999), Springer, New York 81-106
3. Hu T.-L., and Sheu J.-B. A fuzzy-based customer classification method for advanced demand-responsive logistical distribution operations. Fuzzy Sets Syst. 139 (2003) 431-450
4. Fisher M.L., and Jaikumar R. A generalized assignment heuristic for vehicle routing. Networks 11 (1981) 109-124
5. Solomon M.M., and Desrosiers J. Time window constrained routing and scheduling problems: a survey. Transport. Sci. 22 (1988) 1-13
6. Altinkemer K., and Gavish B. Heuristics for delivery problems with constraint error guarantees. Transport. Sci. 24 (1990) 294-297
7. Bramel J., and Simchi-Levi D. A location-based heuristic for general routing problems. Oper. Res. 43 (1995) 649-660
8. Dror M., Laporte G., and Trudeau P. Vehicle routing with stochastic demands: properties and solution frameworks. Transport. Sci. 23 (1989) 166-176
9. Bertsimas D.J., Chervi P., and Peterson M. Computational approaches to stochastic vehicle routing problems. Transport. Sci. 29 (1995) 342-352
10. Gendreau M., Laporte G., and Seguin R. Stochastic vehicle routing. Eur. J. Oper. Res. 88 (1996) 3-12
11. Secomandi N. Comparing neuro-dynamic programming algorithms for the vehicle routing problem with stochastic demands. Comput. Oper. Res. 27 (2000) 1201-1225
12. Gendreau M., Hertz A., Laporte G., and Stan M. A generalized insertion heuristic for the traveling salesman problem with time windows. Oper. Res. 46 3 (1998) 330-346
13. Powell W.B. An operational planning model for the dynamic vehicle allocation problem with uncertain demands. Transport. Res. B 21 3 (1987) 217-232
14. C.A. Hane, C. Barnhart, E.L. Johnson, R.E. Marsten, G.L. Nemhauser, G. Sigismondi, A fleet assignment problem: solving a large-scale integer problem, Technical Report, Report Series 92-04, School of Industrial and System Engineering, Georgia Institute of Technology, 1994.
15. Psaraftis H.N. Dynamic vehicle routing. Ann. Oper. Res. 61 (1995) 143-164
16. Powell W.B., Jaillet P., and Odoni A. Stochastic and dynamic networks and routing. In: Ball M.O., Magnanti T.L., Monma C.L., and Nemhauser G.L. (Eds). Network Routing. Handbooks in Operations Research and Management Science vol. 8 (1995), Elsevier, Amsterdam 141-296
17. W.B. Powell, T. Carvalho, Dynamic control of logistics queuing network for large-scale fleet management, Report 96-01, Department of Civil Engineering and Operations Research, Princeton University, 1996.
18. Powell W.B., and Carvalho T.A. Dynamic control of multicommodity fleet management problems. Eur. J. Oper. Res. 98 (1997) 522-541
19. Regan A.C., Mahmassani H.S., and Jaillet P. Dynamic decision making for commercial fleet operations using real-time information. Transport. Res. Record 1537 (1996) 91-97
20. H.S. Mahmassani, Y. Kim, P. Jaillet, Local optimization approaches to solve dynamic commercial fleet management problems, Paper presented at the 79th Annual Meeting of the Transportation Research Board, Washington, DC, January 2000.
21. Godfrey G.A., and Powell W.B. An adaptive dynamic programming algorithm for dynamic fleet management, I: single period travel times. Transport. Sci. 36 1 (2002) 21-39
22. Godfrey G.A., and Powell W.B. An adaptive dynamic programming algorithm for dynamic fleet management, II: multiperiod travel times. Transport. Sci. 36 1 (2002) 40-54
23. Powell W.B., Shapiro J.A., and Simao H.P. An adaptive dynamic programming algorithm for the heterogeneous resource allocation problem. Transport. Sci. 36 2 (2002) 231-249
24. Y. Shan, A Dynamic Multicommodity Network Flow Model for Real-Time Optimal Rail Freight Car Management, Ph.D. Dissertation, Princeton University, 1985.
25. K.C. Chih, A Real Time Dynamic Optimal Freight Car Management Simulation Model of the Multiple Railroad, Multicommodity, Temporal Spatial Network Flow Problem, Ph.D. Dissertation, Princeton University, 1986.
26. Hamacher A., Hochstattler W., and Moll C. Tree partitioning under constraints-clustering for vehicle routing problems. Discr. Appl. Math. 99 (2000) 55-69
27. Bowersox D.J., and Closs D.J. Logistical operations integration. In: Closs D.J. (Ed). Logistical Management: The Integrated Supply Chain Process (1996), McGraw-Hill, Singapore 41-44
28. Geoffrion A.M., and Graves G.M. Multicommodity distribution system designed by benders decomposition. Manage. Sci. 20 5 (1974) 822-844
29. Burns L.D., Hall R.W., Blumenfeld D.E., and Daganzo C.F. Distribution strategies that minimize transportation and inventory costs. Oper. Res. 33 3 (1985) 469-490
30. Arntzen B.C., Brown G.G., Harrison T.P., and Trafton L.L. Global supply chain management at digital equipment corporation. Interfaces 25 1 (1995) 69-93
31. M.H. Cole, Service Considerations and the Design of Strategic Distribution Systems, Ph.D. Thesis, Georgia Institute of Technology, USA, 1995.
32. Priber U., and Kretzschmar W. Inspection and supervision by means of hierarchical fuzzy classifiers. Fuzzy Sets Syst. 85 (1997) 263-274
33. Devillez A., Billaudel P., and Villermain Lecolier G. A fuzzy hybrid hierarchical clustering method with a new criterion able to find the optimal partition. Fuzzy Sets Syst. 128 3 (2002) 323-338
34. Hoppner F. Speeding up fuzzy c-means: using a hierarchical data organization to control the precision of membership calculation. Fuzzy Sets Syst. 128 3 (2002) 365-376
35. Sheu J.-B. A fuzzy clustering based approach to automatic freeway incident detection and characterization. Fuzzy Sets Syst. 128 3 (2002) 377-388
36. Tao C.W. Unsupervised fuzzy clustering with multi-center clusters. Fuzzy Sets Syst. 128 (2002) 305-322
37. J.-B. Sheu, Analyses of customer demand attributes for development of a demand-responsive logistics distribution system, Final report NSC 92-2416-H-009-005, National Science Council, Taiwan, 2004.
38. Hoppner F., Klawonn F., Kruse R., and Runkler T. Fuzzy Cluster Analysis: Methods for Classification, Data Analysis and Image Recognition (1999), Wiley, Englewood Cliffs, NJ
39. J.C. Bezdek, Fuzzy Mathematics in Pattern Classification, Ph.D. Thesis, Cornell University, USA, 1973.
40. Hall L.O., Bensaid A.M., Clarke L.P., Velthuizen R.P., Silbiger M.S., and Bezdek J.C. A comparison of neural network and fuzzy clustering techniques in segmenting magnetic resonance images of the brain. IEEE Trans. Neural Networks 3 5 (1992) 672-682
41. Sugeno M., and Yasukawa T. A fuzzy-logic-based approach to qualitative modeling. IEEE Trans. Syst. 24 (1993) 1279-1284
42. Dantzig G.B., Fulkerson D.R., and Johnson S.M. Solutions of large scale traveling salesman problem. Oper. Res. 2 (1954) 393-410
43. Gouveia L., and Pires J.M. The asymmetric traveling salesman problem and a reformulation of the Miller-Tucker-Zemlin constraints. Eur. J. Oper. Res. 112 (1999) 134-146
44. Taniguchi E., Thompson R.G., Yamada T., and Duin R.V. Vehicle routing and scheduling. In: Taniguchi E., Thompson R.G., Yamada T., and Duin R.V. (Eds). City Logistics: Network Modelling and Intelligent Transport Systems (2001), Pergamon, New York 111-135
45. Sheu J.-B. A stochastic modeling approach to dynamic prediction of section-wide inter-lane and intra-lane traffic variables using point detector data. Transport. Res. A 33 2 (1999) 79-100
46. Sheu J.-B., and Ritchie S.G. Stochastic modeling and real-time prediction of vehicular lane-changing behavior. Transport. Res. B 35 7 (2001) 695-716