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2022 | OriginalPaper | Chapter

Driver Equitability and Customer Optimality in Intelligent Vehicle Applications

Author : Martin Aleksandrov

Published in: Progress in Artificial Intelligence

Publisher: Springer International Publishing

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Abstract

We consider classical vehicle routing problems with customer costs, vehicle feasibilities, driver profits, and driver responsiveness. We motivate a new template for these new problems, which first returns some feasible matching between drivers and customers and then some feasible plan for routing the vehicles through their matched locations. Thus, by using this template, we show that bounded equitability for drivers and Pareto optimality for customers can always be achieved in isolation but not always in combination. Finally, we give fixed-parameter tractable routing algorithms for fleet equitability and fleet efficiency.

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previous chapter Generating the Users Geographic Map Using Mobile Phone Data

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Title: Driver Equitability and Customer Optimality in Intelligent Vehicle Applications
Author: Martin Aleksandrov
Publisher: Springer International Publishing
Book: Progress in Artificial Intelligence
Print ISBN: 978-3-031-16473-6

Electronic ISBN: 978-3-031-16474-3

Copyright Year: 2022
DOI: https://doi.org/10.1007/978-3-031-16474-3_26

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