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http://dx.doi.org/10.11627/jkise.2012.35.4.171

A Possible Heuristic for Variable Speed Vehicle Routing Problem with 4 Time Zone  

Moon, Geeju (Department of Industrial and Management Systems Engineering, Dong-A University)
Park, Sungmee (Department of Industrial and Management Systems Engineering, Dong-A University)
Publication Information
Journal of Korean Society of Industrial and Systems Engineering / v.35, no.4, 2012 , pp. 171-178 More about this Journal
Abstract
A possible heuristic to solve metropolitan area vehicle routing problems with variable vehicle speeds is suggested in this research. Delivery hours are classified into 4 different time zones to make variable vehicle speeds no change within the same time zone to make TDVRP simple to solve. The suggested heuristic consists of 2 stages such as initial solution development step and initial solution improvement step. A computer program using C++ is constructed to evaluate the suggested heuristic. Randomly generated vehicle routing problems are used for the experiments. This heuristic could be helpful to logistics companies by increasing delivery efficiencies since the 4 zone classification is taken from the observed traffic information offered by a local government.
Keywords
Vehicle Routing Problem; TDVRP; Traveling Salesman Problem; Combinatorial Optimization;
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Times Cited By KSCI : 2  (Citation Analysis)
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1 Imran, A., Salhi, S., and Wassan, N.A., A Variable Neighborhood-based Heuristic for the Heterogeneous Fleet Vechicle Routing Problem. European Journal of Operational Research, 2009, Vol. 197, No. 2, p 509-518.   DOI   ScienceOn
2 Malandraki, C. and Daskin, M.S., Time Dependent Vehicle Routing Problems : Formulations, Properties and Heuristic Algorithms. Transportation Science, 1992, Vol. 26, No. 3, p 185-200.   DOI
3 Moon, G. and Park, S., Analysis and Reconstruction of Vehicle Speeds to Design an Efficient Time Dependent VRP Heuristic. Journal of the Society of Korea Industrial and Systems Engineering, 2012, Vol. 35, No. 1, p 140-147.
4 Brandao, J., A Deterministic Tabu Search Algorithm for the Fleet Size and Mix Vehicle Routing Problem. European Journal of Operational Research, 2009, Vol. 195, No. 3, p 716-728.   DOI   ScienceOn
5 Magalhaes, J.M. and Sousa, J.P., Dynamic VRP in pharmaceutical distribution a case study. CEJOR 2006, Vol. 14, No. 2, p 177-192.   DOI   ScienceOn
6 Sun, L. and Hu, X., Knowledge representation for the Model of capacitated vehicle routing problems. IEEE 2005, Vol. 0-7695-2504-0, No. 2, p 1110-1114.
7 Gendreau, M., Guertin, F., Potvin, J., and Seguin, R., Neighborhood search heuristics for a dynamic vehicle dispatching problem with pick-ups and deliveries. Transportation Research Part C. 2006, Vol. 14, No. 3, p 157-174.   DOI   ScienceOn
8 Baldacci, R. and Mingozzi, A., Lower bounds and an exact method for the capacitated vehicle routing problem. IEEE, 2006, Vol. 1-4244-0451-7, No. 2, p 1536-1540.
9 Park, S. and Moon, G., A Study on the Walking Time to Drop off Parcels on the Design of VRP Heuristic for Parcel Delivery Services. Journal of the Society of Korea Industrial and Systems Engineering, 2012, Vol. 35, No. 2, p 88-194.
10 Hil, V. and Benton, W.C., Modeling Intra-City Time-Dependent Travel Speeds for Vehicle Scheduling Problems. Journal of Operational Research Society, 1992, Vol. 43, No. 4, p 343-351.
11 Bell, W.J., Dalberto, L.M., Fisher, M.L., Greenfield, A.J., Jaikumar, R., Kedia, P., Mack, R.G., and Prutzman, P.J., Improving the Distribution of Industrial Gases with an On-Line Computerized Routing and Scheduling Optimizer. Interfaces, 1983, Vol. 13, No. 6, p 4-23.   DOI   ScienceOn