Reducing the Minimal Fleet Size by Delaying Individual Tasks

Journal article (2024)

Authors

M. Kronmüller Learning & Autonomous Control - Mechanical, Maritime and Materials Engineering
Andres Fielbaum Learning & Autonomous Control - Mechanical, Maritime and Materials Engineering
J. Alonso-Mora Learning & Autonomous Control - Mechanical, Maritime and Materials Engineering
Research Group
Learning & Autonomous Control (Mechanical, Maritime and Materials Engineering) (TU Delft)
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Published Date

2024

Language

English

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Faculty

Mechanical, Maritime and Materials Engineering

Department

Cognitive Robotics

Research Group

Learning & Autonomous Control

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.

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