Cantarella, G.E., Febbraro, A.D. and Gangi, M.D. (2019) Stochastic Multi-Vehicle Assignment to Urban Transportation Networks. 2019 6th International Conference on Models and Technologies for Intelligent Transportation Systems, Cracow, 5-7 June 2019, 1-8.
https://doi.org/10.1109/MTITS.2019.8883351

has been cited by the following article:

• TITLE: A Multi-Vehicle, Multi-Factory Assignment Problem: A Case of Coca-Cola Bottling Company at Ahinsan and Spintex-Ghana

  AUTHORS: Sampson T. Appiah, Dominic Otoo, Bernard A. Adjei

  KEYWORDS: Mixed-Integer, Quadratic, Multi-Vehicle, Transportation, Multi-Factory

  JOURNAL NAME: American Journal of Operations Research, Vol.10 No.5, September 25, 2020

  ABSTRACT: Determining the type of vehicles to transport goods between multiple factories and numerous distributors with different demands is one of the major logistic decisions that have to be made by industry players to reduce the cost of operations. A Mixed-Integer Quadratic Programming (MIQP) model was used to optimally distribute goods to 105 distributors from two factories across Ghana. The formulated model and analysis show that the existence of multiple vehicles in a fleet purposely for long hauling of goods also renders an optimal minimum cost as compared to a single-vehicle fleet. This optimum minimum cost accounts for 0.2066 of the total cost incurred by the two factories. This resulted in a 25% reduction in transportation cost. Again, a single-vehicle fleet with loading capacity within the mean value of all individual demands gave a minimum cost next to the optimal minimum.