PT Journal
AU Hormes, F
   Siala, A
   Lieb, C
   Fottner, J
TI Fleet Sizing of Dynamically Routed In-plant Milk-run Vehicles Based on a Genetic Algorithm
SO Logistics Journal : Proceedings
PY 2020
VL 2020
IS 12
DI 10.2195/lj_Proc_hormes_en_202012_01
DE Genetische Algorithmen; In-plant milk-run; Routenzugsysteme; Routing-Probleme; Steuerungsstrategien; control strategies; genetic algorithms; routing problems
AB In-plant milk-run (MR) systems enable efficient supply of assembly lines in small lot sizes. One major chal-lenge for MR systems are demand fluctuations and short-term changes within schedules. Dynamic control strategies aim at increasing flexibility and efficiency of MR systems in volatile environments. This paper presents an application-oriented approach for determining the fleet size of an MR system with dynamically controlled routes based on a genetic algorithm. The approach is evaluated and discussed using a case study from a commercial vehicle manufacturer. The results show that the approach ena-bles effective analytical dimensioning of MR systems with dynamic routes. In addition, the case study indicates that the implementation of dynamic routes can lead to a reduction in fleet size.
ER