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An Adaptive Large Neighborhood Search for the Larger-scale Multi Depot Green Vehicle Routing Problem with Time Windows by Muyang Wen; Wei Sun; Yang Yu; Jiafu Tang; Kaku Ikou is a Environmental Science article available to read on EtoBox.

What is An Adaptive Large Neighborhood Search for the Larger-scale Multi Depot Green Vehicle Routing Problem with Time Windows about?

Global warming is a serious problem presently faced by human society, and CO2 is a major concern as a greenhouse gas (GHG), especially as the amount of atmospheric CO2 has been steadily increasing in recent years. Multi-depot model of vehicle routing has sparked widespread interest among researchers as an effective means of reducing cost comprising carbon emissions, fuel consumption, vehicles rental, and driver salaries. In this paper, we developed an improved adaptive large neighborhood search (ALNS) algorithm to efficiently solve large-scale instances of the multi-depot green vehicle routing problem with time windows (MDGVRPTW), based on the characteristics of the multi-depot model, and the formulation of carbon emissions from customers. For the destroy operation, three problem-specific destroy operators that took advantage of the structure of the multi-depot model and the calculation formula of carbon emissions, were deliberately tailored for the MDGVRPTW. The operators could rapidly remove customers causing significant carbon emissions, which enabled these customers to be better positioned in future repair operations. For the repair operation, a noise-greedy repair operator was

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Author

Muyang Wen; Wei Sun; Yang Yu; Jiafu Tang; Kaku Ikou

Publisher

Elsevier BV

Published

2022

Language

EN

Field

Environmental Science (Physical Sciences)