Article
A VEHICLE ROUTING PLANNING SYSTEM FOR GOODS DISTRIBUTION IN URBAN AREAS USING GOOGLE MAPS AND GENETIC ALGORITHM
DOI: 10.7708/ijtte.2016.6(2).04
6 / 2 / 159-167 Pages
Author(s)
Teodor Dimitrov Berov - Todor Kableshkov University of Transport, Faculty of Transport Management, Sofia, Bulgaria -
Abstract
This article presents a system aimed at generating optimized vehicles routes - the vehicle routing problem with time windows (VRPTW) based on using a Google Mapsâ„¢ network data and imperialist competitive algorithm meta-heuristic. The vehicle routing problem with time windows is an important problem in the supply chain management. It copes with route scheduling and the distribution of goods from the distribution center to geographically dispersed customers in urban areas by a fleet of vehicles with constrained capacities. The system was tested for urban goods distribution in Sofia, Bulgaria - 35 retailers, warehouse, two types of vehicles (capacity) and a working day.
Number of downloads: 2341
References:
Atashpaz-Gargari, E.; Lucas, C. 2007. Imperialist competitive algorithm: an algorithm for optimization inspired by imperialistic competition, IEEE Congress on Evolutionary Computation, 4661-4667.
Christophe, D. et al. 2010. A GRASPxELS with Depth First Search Split Procedure for the HVRP, Research Report LIMOS/RR-10-08.
Google Maps JavaScript API. Available from Internet: https://developers.google.com/maps/documentation/javascript/.
Hari, S.; Gangesh, M.; Kamal, P. 2014. GIS Based Solution of Multi-Depot Capacitated Vehicle Routing Problem with Time Window Using Tabu Search Algorithm, International Journal for Traffic and Transportation Engineering, 3(2): 83-100.
Karagyozov, K.; Berov, T. 2014. Prilozhenie na imperialisticheski konkurenten algoritam za optimizirane marshrutizatsiyata na prevoznite sredstva, Mehanika, transport, komunikatsii, 3(1): 63-68. (In Bulgarian: Карагьозов, K.; Беров, Т. 2014. Приложение на империалиÑтичеÑки конкурентен алгоритъм за оптимизиране маршрутизациÑта на превозните ÑредÑтва, Механика, транÑпорт, комуникации, 3(1): 63-68.)
NEO/VRP. Available from Internet: http://neo.lcc.uma.es/vrp/.
Paraskevopoulos, D.C. et al. 2008. Reactive Variable Neighborhood Tabu Search for Heterogeneous Fleet Vehicle Routing and Scheduling Problems, Journal of Heuristics, 14(5): 425-455.
Prins, C. 2004. A simple and efective evolutionary algorithm for the vehicle routing problem, Computer and Operations Research, 31(12): 1985-2002.
Todorova, M.; Djaleva, A. 2014. Za menidjarite v tovarnija avtomobilen transport, Sofia. (In Bulgarian: Тодорова, Ðœ.; Джалева, Ð. 2014. За мениджърите в Ñ‚Ð¾Ð²Ð°Ñ€Ð½Ð¸Ñ Ð°Ð²Ñ‚Ð¾Ð¼Ð¾Ð±Ð¸Ð»ÐµÐ½ транÑпорт, СофиÑ.)
Toth, P.; Vigo, D. 2002. The Vehicle Routing Problem (Eds.), SIAM Monographs on Discrete Mathematics and Applications, Philadelphia.
Quoted IJTTE Works
There is no quoted studies.
Related Keywords