Optimizing Vehicle Replacement in Sustainable Urban Freight Transportation Subject to Presence of Regulatory Measures

Parisa Ahani, Amílcar Arantes (), Rohollah Garmanjani and Sandra Melo
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Parisa Ahani: CERIS, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais 1, 1049-001 Lisboa, Portugal
Amílcar Arantes: CERIS, Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais 1, 1049-001 Lisboa, Portugal
Rohollah Garmanjani: Center for Mathematics and Applications (NOVA Math), FCT NOVA, 2829-516 Caparica, Portugal
Sandra Melo: CEiiA, Center of Engineering and Development, Av. Dom Afonso Henriques 1825, 4450-017 Matosinhos, Portugal

Sustainability, 2023, vol. 15, issue 16, 1-18

Abstract: Since the 1990s, studies and pilot tests have been conducted to reduce traffic, accidents, and pollution due to urban freight transport (UFT). These ended up in several policies, regulations, and restrictions for UFT, such as low emission zones, delivery time windows, and vehicle size and weight restrictions. However, issues in UFT under regulatory measures still persist. This study introduces an optimization framework for deriving an optimal combination of various types of vehicles with different capacities for vehicle replacement with UFT. This framework allows an understanding of how an urban freight company with a limited budget efficiently satisfies its freight demand within an urban area in the presence of regulatory measures by urban administrators. The introduced formulation, which is mixed-integer linear programming, will assist the operator in choosing the best investment strategy for introducing new vehicles of certain types and sizes, for operation in different zones, into its fleet while gaining economic benefits and having a positive impact on the liveability of the urban area. Furthermore, an elasticity analysis is performed to consider the effects of specific uncertain parameters on the total cost. The numerical results show that the share of electric vehicles in the fleet increases, and they are more competitive than diesel vehicles.

Keywords: urban freight transport; freight fleet optimization; vehicle replacement; electric vehicle; regulatory measures; mixed-integer linear programming (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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