Vehicle-routing problems (VRP), which can be considered a generalization of TSP, have been studied in depth. Many variants of the problem exist, most of them trying to find a set of routes with the shortest distance or time possible for a fleet of vehicles. This paper combines two important variants, the stochastic time-dependent VRP and the multi-objective VRP. A genetic algorithm for solving the problem is introduced. A comparison of two fitness functions, with significant difference in computational time, is also presented. Finally, a comparison of solution selection based on TOPSIS method and the two fitness functions is also examined. Results show that a significant decrease in running time, minutes compared to hours, can be achieved, with no impact on the final results of the algorithm. Multi-Objective Stochastic VRP – Fitness Calculation and Algorithm Converges Using a Generic Genetic Algorithm (PDF Download Available). Available from: https://www.researchgate.net/publication/268629359_Multi-Objective_Stochastic_VRP_-_Fitness_Calculation_and_Algorithm_Converges_Using_a_Generic_Genetic_Algorithm [accessed Jan 13, 2016].
|Number of pages||15|
|Journal||International Journal of Computer Systems|
|State||Published - 2014|