Exploring airport traffic capability using Petri net based model Reggie Davidrajuh a,1 , Binshan Lin b,⇑ a University of Stavanger, P.O. Box 8002, 4036 Stavanger, Norway b Louisiana State University in Shreveport, Shreveport, LA 71115, USA article info Keywords: Expert systems Airport traffic Petri net GPenSIM abstract The first part of the paper introduces a novel tool for modeling and simulation of discrete event system. This tool called GPenSIM is a Petri net based simulator and offers significant benefits to model builders such as flexibility to include diverse libraries, ease of extending the models, and ease of programming. The second part of the paper presents a case study on modeling and optimization of airport traffic man- agement; this study is to explore air traffic management capability of Evenes airport in Norway. The case study shows that with GPenSIM, modeling and simulation problems of large industrial discrete event sys- tems can be done. Future research directions are discussed as well. Ó 2011 Elsevier Ltd. All rights reserved. 1. Introduction Petri net is being widely accepted by the research community for modeling and simulation of discrete event-driven systems, mainly due to Petri net’s rigorous modeling techniques (Cheng & Yang, 2009; Shih, Chiang, & Lin, 2007). There are a number of Petri net tools available for free academic use; see PNWorld (Petri Net World, 2009) for a list of tools. These tools are advanced tools flex- ible enough to model complex and large systems. This paper pre- sents the development of a novel Petri net simulator. The major reasons for building a new simulator are:  Flexible: the simulator should enable easy integration with other libraries and tools, so that developing hybrid models (e.g. Fuzzy Petri nets, by integrating Petri net with Fuzzy Logic) becomes easy.  Extensible: the simulator should enable users writing their own extensions, either extending or rewriting the existing functions or developing new functions.  Easy of use: for those who does not want to use mathematics when developing a model, the tool should provide a natural lan- guage user interface, so that the mathematical details are abstracted away from the user. General-purpose Petri net simulator (GPenSIM, 2009) is devel- oped in order to satisfy the three criteria stated above (flexible, extensible, and ease of use). GPenSIM is realized as toolbox for the MATLAB platform, so that diverse toolboxes that available in the MATLAB environment (e.g. Fuzzy Logic Toolbox, Control Sys- tems Toolbox) can be used in the models that are developed with GPenSIM. In this paper, GPenSIM is introduced. Secondly, a case study is illustrated on modeling an airport with Petri net for exploring its traffic capability. 2. Existing tools for discrete event simulation Many existing tools satisfy some of the three criteria men- tioned. Automata, Stateflow, and Petri nets are the well-known tools used for simulation of discrete event systems. Though auto- mata have a strong footing in computer science, the serious short- coming with it is the lack of structure – the ability to modularize a system (decompose a system into modules) (Avinor, 2009). State- flow is commercial software that runs in MATLAB environment (Extend, 2009). Stateflow is similar to Petri net; converting a Petri net model of a discrete event system into a Stateflow model and vice versa is easy. However, learning Stateflow, with its syntactic, semantic, and graphical details, is much more difficult than learn- ing Petri net. In addition, Stateflow also demands some knowledge of Simulink, in addition to MATLAB. Petri net has been widely accepted for modeling and simulation of discrete event systems and there is a number of Petri net tools available free-of-charge for academic usage (Petri Net World, 2009). These tools are sophisticated tools flexible enough to model complex and large systems. However, these tools are stand-alone systems, and for integrating the functions of these tools with other tools or libraries, one need to program in either high-level lan- guages like Java or C++, or use XML as an intermediary (Lattila, Hilletofth, & Lin, 2010; Tucker, 2008). Thus seamless integration 0957-4174/$ - see front matter Ó 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.eswa.2011.02.134 ⇑ Corresponding author. Tel.: +1 318 797 5025; fax: +1 318 797 5127. E-mail addresses: reggie.davidrajuh@uis.no (R. Davidrajuh), Binshan.Lin@ LSUS.edu (B. Lin). 1 Tel.: +47 518 317 00. Expert Systems with Applications 38 (2011) 10923–10931 Contents lists available at ScienceDirect Expert Systems with Applications journal homepage: www.elsevier.com/locate/eswa