Creating and Validating a Microscopic Pedestrian Simulation to Analyze an Airport Security Checkpoint

Aim of this simulation case study is to analyze waiting times and throughput at the security checkpoint of an international medium sized airport. The simulations shall provide the airport operator with the ability to easily change main impact parameters of an airport security checkpoint e.g. to test new security procedures, a flightplan with more passengers and also to optimize the security operation schedule.

Linking Symbiotic Simulation to Enterprise Systems: Framework and Applications

Symbiotic simulation is a paradigm that emphasizes a close association between a simulation system and a physical system, which is usually beneficial to at least one of them and not necessarily detrimental to the others. Aimed at extending previous work in symbiotic simulation, this paper proposes a framework of symbiotic simulation that can be used to improve the performance of a production system controlled by an enterprise system.

Particle Filtering Using Agent-based Transmission Models

Dynamic models are used to describe the spatio-temporal evolution of complex systems. It is frequently difficult to construct a useful model, especially for emerging situations such as the 2003 SARS outbreak.Here we describe the application of a modern predictor-corrector method – particle filtering – that could enable relatively quick model construction and support on-the-fly correction as empirical data arrives.

An Agent-based Approach for Modeling the Effect of Learning Curve on Labor Productivity

The labor-intensive nature of construction projects requires proper management and efficient utilization of labor resources. Improvement of labor productivity can enhance project performance and thereby lead to substantial time and cost savings. Several studies focused on identifying the effect of different factors on labor productivity, whereby the learning curve factor proved of paramount importance. Although previous research efforts developed models to represent the learning curve effect using traditional simulation approaches such as System Dynamics (SD) and Discrete Event Simulation (DES), none of these studies used Agent-Based Modeling (ABM) techniques. This study takes the initial steps and presents work targeted at analyzing the effect of learning on labor productivity using ABM.

Use of agent-based modelling to predict benefits of cleaner fish in controlling sea lice infestations on farmed Atlantic salmon

Sea lice, Lepeophtheirus salmonis, are ectoparasites of farmed and wild salmonids. Infestations can result in significant morbidity and mortality of hosts in addition to being costly to control. Integrated PEST management programmes have been developed to manage infestations, and in some salmon farming areas, these programmes include the use of wrasse. To explore at what densities wrasse should be stocked in order to meet specific control targets, an individual-based model was built to simulate sea lice infestation patterns on a representative salmonid host. It was found that the wrasse can effectively control sea lice, and the densities of wrasse needed for effective control depend upon the source of the infestation and the targeted level of control.

Simulating Construction Bidding Using Agent-Based Modeling

Competitive bidding is the main mechanism for allocation of construction projects and consequently price determination of the construction services in the A/E/C industry. While different aspects of construction bidding have been studied in the literature, there is still a need for developing a comprehensive model that captures the complex dynamics of bidding environment by considering interactions among its components, most importantly construction contractors. This paper discusses the advantages of agent-based modeling in simulating the construction bidding process over the previously applied methodologies.

Major City Evacuation Planning Using Simulation Modeling

Disaster, whether manmade or natural, can have a catastrophic impact on a populated area. Sometimes, the disaster is so devastating that it requires a large-scale evacuation. As a result, evacuation plans have become a necessity. One such evacuation plan is the regional hub reception center (RHRC), which will help evacuate the careless population when an evacuation is needed. Using AnyLogic as a simulation modeling software, an RHRC model was developed to test the efficiency of the proposed plan.

Simulation Software Comparison

The comparison of AnyLogic and other simulation tools is inspired by ORMS Today Simulation Software Survey published in October, 2015. “ORMS Today” journal, published by a global institute of operational management and analytics “INFORMS”, completed a detailed comparison of popular tools for discrete-event modelling. In 2015 it was supported by 31 developers and 55 tools. Data, used in the research, was kindly presented by the developers themselves.

Agent-based population model used to identify and evaluate dog population management strategies

Developing countries are faced with finding novel and humane ways to permanently reduce and control their dog population. Agent-based models developed to describe dog populations represent a unique, platform for using computer based simulation to identify control strategies with the greatest potential for success, aid in the design of more effective control measures, and provide a means to evaluate the success of different interventions.