A Novel Approach for Vehicle Fleet Sizing and Allocation Under Uncertain Demand

PRESSER, DEMIAN J.; CAFARO, VANINA G.; CAFARO, DIEGO C.

Toulouse

Conferencia; 32nd European Symposium on Computer Aided Process Engineering; 2022

ESCAPE CONFERENCE SECRETARIAT

In this work, we propose a novel optimization model based on mixed integer linearprogramming (MILP) whose goal is to optimize the size and allocation of vehicle fleetsunder uncertain demand patterns. In contrast to previous contributions, the probabilityof meeting demand is a model decision and the approach is able to handle anyprobability distribution to characterize the number of trips required in the network.Furthermore, fleet procurement and contracting decisions for alternative types ofvehicles are integrated into the model. The formulation allows to considerably reducecosts by avoiding oversizing and can be adapted to diverse demand characterizationsand contracting terms from different industries. The proposed approach is able to tackleproblems of real dimensions in very low computational times in comparison to previousworks. A real-world case study involving maintenance operations in geographicallyspread assets is addressed to highlight the model capabilities and draw conclusions.