Reducing the Minimal Fleet Size by Delaying Individual Tasks
M. Kronmüller (TU Delft - Learning & Autonomous Control)
Andres Fielbaum (TU Delft - Learning & Autonomous Control)
J. Alonso-Mora (TU Delft - Learning & Autonomous Control)
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Abstract
This work formally defines the problem of fleet sizing with delays (FSD), where the option of delaying individual tasks within fleet sizing is considered. We prove that the FSD problem is NP-hard and solve a formulation of the FSD problem as a mixed integer linear problem (MILP). We then analyze the proposed method in detail in an abstract case and validate it in a case study of taxi rides in Manhattan. We show that fleet sizes can be decreased significantly and that the trade-off space of the number of required vehicles to execution time and added delay can be enlarged.