@article {1449, title = {Modeling the pharmacodynamics of nandrolone doping drug and implications for anti-doping testing}, journal = {System Dynamics Review}, volume = {36}, year = {2020}, pages = {467-496}, abstract = {

Abstract We model the pathways of nandrolone in the body, an anabolic steroid widely used as a performance enhancing drug (PED). The model generates the dynamics of nandrolone and its metabolites. PED tests check for the presence of a primary metabolite of nandrolone, 19-NA in urine. To cheat in these tests, PED users typically use inhibitors that reduce the urinary concentration of 19-NA. One such inhibitor is finasteride. Finasteride{\textquoteright}s main effect in the body is the inhibition of reductase enzymes that turn nandrolone into its metabolite 19-NA. To capture this effect, we include structures for finasteride and reductase enzymes in the model. The model is tested by fundamental structure validity tests. We also show that the model behavior is consistent with experimental data in the literature. We finally investigate the potential ways by which the drug users may cheat in PED tests and make suggestions for improved testing as counter-measures. {\textcopyright} 2021 System Dynamics Society

}, doi = {https://doi.org/10.1002/sdr.1672}, url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/sdr.1672}, author = {Sahin, {\"O}zge and Feyyaz {\c S}ent{\"u}rk and Yaman Barlas and Yasarcan, Hakan} } @article {1493, title = {The moderating impact of supply network topology on the effectiveness of risk management}, journal = {International Journal of Production Economics}, volume = {197}, year = {2018}, pages = {13-26}, abstract = {

While supply chain risk management offers a rich toolset for dealing with risk at the dyadic level, less attention has been given to the effectiveness of risk management in complex supply networks. We bridge this gap by building an agent based model to explore the relationship between topological characteristics of complex supply networks and their ability to recover through inventory mitigation and contingent rerouting. We simulate upstream supply networks, where each agent represents a supplier. Suppliers{\textquoteright} connectivity patterns are generated through random and preferential attachment models. Each supplier manages its inventory using an anchor-and-adjust ordering policy. We then randomly disrupt suppliers and observe how different topologies recover when risk management strategies are applied. Our results show that topology has a moderating effect on the effectiveness of risk management strategies. Scale-free supply networks generate lower costs, have higher fill-rates, and need less inventory to recover when exposed to random disruptions than random networks. Random networks need significantly more inventory distributed across the network to achieve the same fill rates as scale-free networks. Inventory mitigation improves fill-rate more than contingent rerouting regardless of network topology. Contingent rerouting is not effective for scale-free networks due to the low number of alternative suppliers, particularly for short-lasting disruptions. We also find that applying inventory mitigation to the most disrupted suppliers is only effective when the network is exposed to frequent disruptions; and not cost effective otherwise. Our work contributes to the emerging field of research on the relationship between complex supply network topology and resilience.

}, keywords = {Agent-based modelling, Complex supply networks, Contingent rerouting, Inventory mitigation, Random networks, Scale-free networks, Supply chain risk management}, issn = {0925-5273}, doi = {https://doi.org/10.1016/j.ijpe.2017.12.013}, url = {https://www.sciencedirect.com/science/article/pii/S092552731730419X}, author = {Anna Ledwoch and Yasarcan, Hakan and Alexandra Brintrup} } @article {edali2014mathematical, title = {A Mathematical Model of the Beer Game}, journal = {Journal of Artificial Societies and Social Simulation}, volume = {17}, number = {4}, year = {2014}, pages = {jasss{\textendash}soc}, publisher = {Journal of Artificial Societies and Social Simulation}, author = {Edali, Mert and Yasarcan, Hakan} } @article {1497, title = {A Mathematical Model of the Beer Game}, journal = {Journal of Artificial Societies and Social Simulation}, volume = {17}, year = {2014}, pages = {2}, abstract = {

The beer production-distribution game, in short {\textquotedblleft}The Beer Game{\textquotedblright}, is a multiplayer board game, where each individual player acts as an independent agent. The game is widely used in management education aiming to give an experience to the participants about the potential dynamic problems that can be encountered in supply chain management, such as oscillations and amplification of oscillations as one moves from downstream towards upstream echelons. The game is also used in numerous scientific studies. In this paper, we construct a mathematical model that is an exact one-to-one replica of the original board version of The Beer Game. We apply model replication principles and discuss the difficulties we faced in the process of constructing the mathematical model. Accordingly, the model is presented in full precision including necessary assumptions, explanations, and units for all parameters and variables. In addition, the adjustable parameters are stated, the equations governing the artificial agents{\textquoteright} decision making processes are mentioned, and an R code of the model is provided. We also shortly discuss how the R code can be used in experimentation and how it can also be used to create a single-player or multi-player beer game on a computer. Our code can produce the exact same benchmark cost values reported by Sterman (1989) verifying that it is correctly implemented. The mathematical model and the R code presented in this paper aims to facilitate potential future studies based on The Beer Game.

}, keywords = {Acquisition Lag, artificial agents, beer game, Mathematical Model, Replication, System Dynamics}, issn = {1460-7425}, doi = {10.18564/jasss.2555}, url = {http://jasss.soc.surrey.ac.uk/17/4/2.html}, author = {Edali, Mert and Yasarcan, Hakan} } @conference {barlas2001method, title = {A Method For Finding Equilibrium Points of a Non-Linear Dynamic Model}, booktitle = {The 19th International System Dynamics Conference, Atlanta, Georgia, USA}, year = {2001}, publisher = {System Dynamics Society (http://www.systemdynamics.org/conferences/2001)}, organization = {System Dynamics Society (http://www.systemdynamics.org/conferences/2001)} }