Comparing simulation output accuracy of discrete event and agent based models: a quantitative approach


Autoria(s): Abdul Majid, Mazlina; Aickelin, Uwe; Siebers, Peer-Olaf
Data(s)

2009

Resumo

In our research we investigate the output accuracy of discrete event simulation models and agent based simulation models when studying human centric complex systems. In this paper we focus on human reactive behaviour as it is possible in both modelling approaches to implement human reactive behaviour in the model by using standard methods. As a case study we have chosen the retail sector, and here in particular the operations of the fitting room in the women wear department of a large UK department store. In our case study we looked at ways of determining the efficiency of implementing new management policies for the fitting room operation through modelling the reactive behaviour of staff and customers of the department. First, we have carried out a validation experiment in which we compared the results from our models to the performance of the real system. This experiment also allowed us to establish differences in output accuracy between the two modelling methods. In a second step a multi-scenario experiment was carried out to study the behaviour of the models when they are used for the purpose of operational improvement. Overall we have found that for our case study example both, discrete event simulation and agent based simulation have the same potential to support the investigation into the efficiency of implementing new management policies.

Formato

application/pdf

Identificador

http://eprints.nottingham.ac.uk/1240/1/majid2009a.pdf

Abdul Majid, Mazlina and Aickelin, Uwe and Siebers, Peer-Olaf (2009) Comparing simulation output accuracy of discrete event and agent based models: a quantitative approach. Proceedings of the Summer Computer Simulation Conference, 2009 . pp. 177-184.

Idioma(s)

en

Publicador

Association for Computing Material

Relação

http://eprints.nottingham.ac.uk/1240/

http://dl.acm.org/citation.cfm?id=2349508&picked=prox&CFID=145836109&CFTOKEN=59616132

Tipo

Article

PeerReviewed