Transport management and vehicle routing problems play a strong role on a company’s efficiency and competitiveness. In the food sector, the complexity of the problem grows because of strict constraints. This paper addresses the dairy transportation problem and in particular tries to optimize the milk collection process of a real company. A two-step approach has been proposed to test the current system and solve the routing problem. First, starting from the “As is” collection tours, a travel salesman problem has been modelled. Later, the Nearest Neighbor algorithm has been implemented in order to find a global optimal solution. Finally, a stochastic simulation model integrates the solutions of the previous step in order to test the feasibility of the outcomes, primarily in terms of their capability to meet the time constraints of the tours. Results show that the greedy approach allows less vehicles to be involved, with a good potential on annual cost saving. On the other hand, the simulation outcomes highlight a borderline case, which is not always in line with the time constraints of the problem.

The milk collection problem with time constraint: an optimization study integrating simulation

Marta Rinaldi
;
2020

Abstract

Transport management and vehicle routing problems play a strong role on a company’s efficiency and competitiveness. In the food sector, the complexity of the problem grows because of strict constraints. This paper addresses the dairy transportation problem and in particular tries to optimize the milk collection process of a real company. A two-step approach has been proposed to test the current system and solve the routing problem. First, starting from the “As is” collection tours, a travel salesman problem has been modelled. Later, the Nearest Neighbor algorithm has been implemented in order to find a global optimal solution. Finally, a stochastic simulation model integrates the solutions of the previous step in order to test the feasibility of the outcomes, primarily in terms of their capability to meet the time constraints of the tours. Results show that the greedy approach allows less vehicles to be involved, with a good potential on annual cost saving. On the other hand, the simulation outcomes highlight a borderline case, which is not always in line with the time constraints of the problem.
2020
978-88-85741-16-4
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11591/439718
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