alexander/urban-meal-delivery-demand-forecasting
1
0
Fork 0
Code Activity

Remove glossary

Browse source
This commit is contained in:
Alexander Hess 2020-11-30 18:42:54 +01:00
commit 96a3b242c0
Signed by: alexander
GPG key ID: 344EA5AB10D868E0
16 changed files with 40 additions and 193 deletions
Download patch file Download diff file Expand all files Collapse all files

6
tex/5_con/4_further_research.tex
View file

@ -19,11 +19,11 @@ Thus, we suggest conducting more detailed analyses on how to incorporate model
Future research should also integrate our forecasting system into a predictive
routing application and evaluate its business impact.
This embeds our research into the vast literature on the VRP.
Initially introduced by \cite{dantzig1959}, \gls{vrp}s are concerned with
Initially introduced by \cite{dantzig1959}, VRPs are concerned with
finding optimal routes serving customers.
We refer to \cite{toth2014} for a comprehensive overview.
The two variants relevant for the UDP case are the dynamic VRP and
the pickup and delivery problem (\gls{pdp}).
the pickup and delivery problem (PDP).
A VRP is dynamic if the data to solve a problem only becomes available
as the operations are underway.
\cite{thomas2010}, \cite{pillac2013}, and \cite{psaraftis2016} describe how
@ -39,7 +39,7 @@ Forecasts by our system extend this idea naturally as dummy nodes could be
The concrete case of a meal delivering UDP is contained in a recent
literature stream started by \cite{ulmer2017} and extended by
\cite{reyes2018} and \cite{yildiz2018}: They coin the term meal delivery
routing problem (\gls{mdrp}).
routing problem (MDRP).
The MDRP is a special case of the dynamic PDP where the defining
characteristic is that once a vehicle is scheduled, a modification of the
route is inadmissible.