A simulation approach for multi-stage supply chain optimization to analyze real world transportation effects

Andreas Josef Peirleitner, Klaus Altendorfer, Thomas Felberbauer

Research output: Chapter in Book/Report/Conference proceedingsConference contributionpeer-review

14 Citations (Scopus)


The cost effective management of a supply chain under stochastic influences, e.g. in demand or the replenishment lead time, is a critical issue. In this paper a multi-stage and multi-product supply chain is investigated where each member uses the (s,Q)-policy for inventory management. A bi-objective optimization problem to minimize overall supply chain costs while maximizing service level for retailers is studied. Optimal parameter levels for reorder points and lot sizes are evaluated. In a first step a streamlined analytical solution approach is tested to identify optimal parameter settings. For real applications, this approach neglects the dynamics and interdependencies of the supply chain members. Therefore a simulation-based approach, combining an evolutionary algorithm with simulation, is used for the optimization. The simulation-based approach further enables the modelling of additional real world transportation constraints. The numerical simulation study highlights the potential of simulation-based optimization compared to analytical models for multi-stage multi-product supply chains.

Original languageEnglish
Title of host publication2016 Winter Simulation Conference
Subtitle of host publicationSimulating Complex Service Systems, WSC 2016
EditorsTheresa M. Roeder, Peter I. Frazier, Robert Szechtman, Enlu Zhou
Number of pages12
ISBN (Electronic)9781509044863
Publication statusPublished - 2 Jul 2016
Event2016 Winter Simulation Conference - Arlington, Virginia, United States
Duration: 11 Dec 201614 Dec 2016

Publication series

NameProceedings - Winter Simulation Conference
ISSN (Print)0891-7736


Conference2016 Winter Simulation Conference
Country/TerritoryUnited States
CityArlington, Virginia


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