This paper studies the Truck Driver Scheduling Problem with Idling Options (TDSP-IO), an extension of the long-haul truck driver scheduling problem with a more comprehensive objective function that accounts for driving cost, fuel cost, and idling cost. The best-known idling option is the widespread practice of keeping the vehicle engine running while the vehicle is not moving, which primarily stems from the drivers'desire to keep their vehicle at an adequate comfort level during breaks. Here, we explore two additional cleaner idling options: resting at an Electrified Parking Space (EPS) or using an Auxiliary Power Unit (APU) while idling. We also account for the initial investments associated with the equipment required for the use of these technologies. We formulate a mathematical model for the TDSP-IO under these three idling options, and we perform extensive computational experiments on realistic benchmark instances. The paper sheds light on the trade-offs between various performance indicators and offers several managerial and policy insights. Our analyses quantify the advantages of using EPSs and APUs, and show that they yield both economical and environmental benefits.

A comparison of three idling options in long-haul truck scheduling

JABALI, OLA;
2016

Abstract

This paper studies the Truck Driver Scheduling Problem with Idling Options (TDSP-IO), an extension of the long-haul truck driver scheduling problem with a more comprehensive objective function that accounts for driving cost, fuel cost, and idling cost. The best-known idling option is the widespread practice of keeping the vehicle engine running while the vehicle is not moving, which primarily stems from the drivers'desire to keep their vehicle at an adequate comfort level during breaks. Here, we explore two additional cleaner idling options: resting at an Electrified Parking Space (EPS) or using an Auxiliary Power Unit (APU) while idling. We also account for the initial investments associated with the equipment required for the use of these technologies. We formulate a mathematical model for the TDSP-IO under these three idling options, and we perform extensive computational experiments on realistic benchmark instances. The paper sheds light on the trade-offs between various performance indicators and offers several managerial and policy insights. Our analyses quantify the advantages of using EPSs and APUs, and show that they yield both economical and environmental benefits.
CO2 emissions, Fuel consumption, Hours of service regulations, Idling, Long-haul transportation, Truck driver scheduling problem, Transportation, Management Science and Operations Research
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1005721
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