MULTI-VEHICLE ROUTE PLANNING FOR CENTRALIZED AND DECENTRALIZED SYSTEMS
MULTI-VEHICLE ROUTE PLANNING FOR CENTRALIZED AND DECENTRALIZED SYSTEMS
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Date
2019
Authors
Patel, Ruchir
Advisor
Herrmann, Jeffrey W
Azarm, Shapour
Azarm, Shapour
Citation
DRUM DOI
Abstract
Multi-vehicle route planning is the problem of determining routes for a set of vehicles
to visit a set of locations of interest. In this thesis, we describe a study of a classical
multi-vehicle route planning problem which compared existing solutions methods on
min-sum (minimizing total distance traveled) and min-max (minimizing maximum
distance traveled) cost objectives. We then extended the work in this study by
adapting approaches tested to generate robust solutions to a failure-robust multi
vehicle route planning problem in which a potential vehicle failure may require
modifying the solution, which could increase costs. Additionally, we considered a
decentralized extension to the multi-vehicle route planning problem, also known as
the decentralized task allocation problem. The results of a computational study show
that our novel genetic algorithm generated better solutions than existing approaches
on larger instances with high communication quality.