Use of agent-based modelling to predict benefits of cleaner fish in controlling sea lice infestations on farmed Atlantic salmon M.L. Groner, R.Cox, G.Gettinby and C.W. Revie

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.
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A Plant-Level, Spatial, Bioeconomic Model Of Plant Disease Diffusion And Control: Grapevine Leafroll Disease Shady S. Atallah, Miguel I. Gómez, Jon M. Conrad, and Jan P. Nyrop, University of New Hampshire

<p>Grapevine leafroll disease threatens the economic sustainability of the grape and wine industry in the United States and around the world. This viral disease reduces yield, delays fruit ripening, and affects wine quality. Although there is new information on the disease spatial-dynamic diffusion, little is known about profit-maximizing control strategies. Using cellular automata, we model the disease spatial-dynamic diffusion for individual plants in a vineyard, evaluate nonspatial and spatial control strategies, and rank them based on vineyard expected net present values. </p>
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The Effect of Cellular Interactions on Cancer Cell Growth Using Evolutionary Game Theory Mihir Paithane, Student, Science, Technology, Engineering, and Math (STEM) Center at Mills E. Godwin High School

In this experiment, game theory was used to assess the interactions between three cell phenotypes usually found in cancer. The three defined cells were autonomous growth cells, invasive and motile malignant cells, and cells that performed anaerobic glycolysis. Based on preset variables in the payoff matrix, analytical equations were deduced that allowed for the analysis of the proportion of autonomous growth and malignant cells in a tumor. AnyLogic was also used to simulate the interactions between cancerous and normal cells.
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A Hybrid Simulation Approach to Dynamic Multi-Skilled Workforce Planning of Production Line Yuan Feng, Wenhui Fan, Tsinghua University. Winter Simulation Conference, 2014.

Workers cross-trained with multiple tasks can improve the workforce flexibility for the plant to handle
variations in workload. Therefore, it is necessary to study the dynamic multi-skilled workforce planning
problem of production line with the application of cross-training method.
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Modeling Human Behavior – An (ID)entity Crisis? Sally C. Brailsford, University of Southampton. Winter Simulation Conference, 2014.

Agent-based modeling (ABM) has gained great popularity in recent years, especially in application areas where human behavior is important, because it opens up the possibility of capturing such behavior in great detail. Hybrid models which combine ABM with discrete-event simulation (DES) are particularly appealing in service industry applications.
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Electric Vehicle Driver Simulation using Agent-Based Modeling Beaudry Kock, Recargo, Inc., 2014

Recargo has been developing an agent-based model with the AnyLogic tool to help us simulate the charging patterns of electric vehicle drivers in California. Our goal is to better understand the potential value from delivering electricity grid services with these vehicles. Development has only been underway for a few weeks, but in that time we’ve been able to use AnyLogic’s accessible interface and Java coding tools to quickly build and test a proof-of-concept model with which we can explore the potential for a more sophisticated and complex effort.
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Using simulation tools for strategic decision making Mark Paich. PricewaterhouseCoopers Technology Forecast 2010, Issue 1.

Dr. Mark Paich provides examples of Decisio’s success in using AnyLogic and other simulation tools to help executives at large enterprises make major transformation decisions.
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Investigating Output Accuracy for a Discrete Event Simulation Model and an Agent Based Simulation Model Mazlina Abdul Majid, Uwe Aickelin, Peer-Olaf Siebers. 2009 INFORMS at University of Warwick, June 25-27, Coventry, U.K.

In this paper, we investigate output accuracy for a Discrete Event Simulation (DES) model and Agent Based Simulation (ABS) model. The purpose of this investigation is to find out which of these simulation techniques is the best one for modelling human reactive behaviour in the retail sector. In order to study the output accuracy in both models, we have carried out a validation experiment in which we compared the results from our simulation models to the performance of a real system. Our experiment was carried out using a large UK department store as a case study.
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Dynamic Learning in Human Decision Behavior for Evacuation Scenarios under BDI Framework Seungho Lee, Young-Jun Son. 2009 INFORMS at University of Warwick, June 25-27, Coventry, U.K.

A novel approach to represent learning in human decision behavior for evacuation scenarios is proposed under the context of an extended Belief-Desire-Intention framework. In particular, we focus on how a human adjusts his perception process (involving a Bayesian belief network) in Belief Module dynamically against his performance in predicting the environment as part of his decision planning function. To this end, a Q-learning algorithm (reinforcement learning algorithm) is employed and further developed.
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Hybrid Simulation and Optimization-Based Capacity Planner for Integrated Photovoltaic Generation with Storage Units Esfandyar M. Mazhari. 2009 Winter Simulation Conference (WSC’09), December 13-16, Austin, TX, USA

Unlike fossil-fueled generation, solar energy resources are geographically distributed and highly intermittent, which makes their direct control difficult and requires storage units. The goal of this research is to develop a flexible capacity planning tool, which will allow us to obtain a most economical mixture of capacities from solar generation as well as storage while meeting reliability requirements against fluctuating demand and weather conditions. The tool is based on hybrid (system dynamics and agent-based models) simulation and meta-heuristic optimization.
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