The paper deals with a hybrid clustering-genetic algorithm that is applied to a rolling-horizon procedure for solving the dynamic vehicle routing problem with time windows. The paper mainly focuses on the advantages of introducing a clustering algorithm jointly with the genetic algorithm. Discussion is supported by numerical tests carried out by simulating the implementation of the procedure to the urban logistic centre of Padova, Italy. Results highlight that introducing clustering criteria to guide a genetic algorithm in the operations of generating the initial population, mutation and cross-over can improve the solution as 20%.
A Heuristic Procedure to Solve an Evolutionary Vehicle Routing Problem with Time Windows / Fusco, Gaetano; M. P., Valentini; V., Conti. - STAMPA. - (2009), pp. 23-28. (Intervento presentato al convegno 2nd WSEAS International Conference on Urban Planning and Transportation tenutosi a Rodi, Grecia nel JUL 22-24, 2009).
A Heuristic Procedure to Solve an Evolutionary Vehicle Routing Problem with Time Windows
FUSCO, Gaetano;
2009
Abstract
The paper deals with a hybrid clustering-genetic algorithm that is applied to a rolling-horizon procedure for solving the dynamic vehicle routing problem with time windows. The paper mainly focuses on the advantages of introducing a clustering algorithm jointly with the genetic algorithm. Discussion is supported by numerical tests carried out by simulating the implementation of the procedure to the urban logistic centre of Padova, Italy. Results highlight that introducing clustering criteria to guide a genetic algorithm in the operations of generating the initial population, mutation and cross-over can improve the solution as 20%.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
