Analysis of Alternative Approaches to Chipotle Mexican Grill’s Service System Using Discrete Event Simulation Brad Guthrie

Chipotle Mexican Grill is a fast causal restaurant chain headquartered in Denver, Colorado. Founded in 1993, they now have over 1,700 locations across America, as well as internationally. Their product line consists of 4 entrée types, 5 protein types, 2 selections of both rice, and beans, 4 types of salsa, and a small selection of extra toppings. Although the “integrity” of their food is a fundamental part of their business strategy, according to both of their co-CEO’s, throughput is also a key factor of focus.
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Evaluation of Agent-Based and Discrete-Event Simulation for Modeling Construction Earthmoving Operations E. Zankoul, H. Khoury and R. Awwad.

One of the most common operations to any construction project is earthwork. In fact, most, if not all, construction projects begin with earthwork activities. These activities require heavy equipment, are generally quite costly and consume a considerable amount of time.
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A Multi-Paradigm Modeling Framework for Modeling and Simulating Problem Situations C. Lynch, J Padilla, S. Diallo, J. Sokolowski, C. Banks, Old Dominion University. Winter Simulation Conference, 2014.

This paper proposes a multi-paradigm modeling framework (MPMF) for modeling and simulating problem situations (problems whose specification is not agreed upon). The MPMF allows for a different set of questions to be addressed from a problem situation than is possible through the use of a single modeling paradigm.
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Quantitative analysis of bidding strategies: a hybrid agent based–system dynamics approach Arash MAHDAVI and Makarand HASTAK, Purdue University

Economic slowdown and construction demand shrinkage reduces the profit backlog for construction contractors and bites into their profit margin. The resulting fierce competition for jobs forces construction companies to look for more sophisticated analytical tools to analyze and improve their bidding strategies. For each contractor, bidding strategy is a decision-making process that is driven by the firm’s financial goals with the final objective of maximizing the firm’s gross profit and surpassing the breakeven point. This paper proposes a methodology to model and analyze different bidding strategies with hybrid agent based-system dynamics (ABSD) simulation.
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A Modular Simulation Model For Assessing Interventions For Abdominal Aortic Aneurysms Christoph Urach, Günther Zauner, Gottfried Endel, Ingrid Wilbacher, Felix Breitenecker, Proceedings of the 2013 Winter Simulation Conference

This paper discusses the development of an individual based simulation of interventions for better treatment of patients with abdominal aortic aneurysms (AAA). The interdisciplinary subject required collaboration of medical doctors, Health Technology Assessment (HTA) experts and modelers.
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An Agent-Based Multi-Scale Wind Generation Model Enrique Kremers, Norbert Lewald (European Institute for Energy Research); Oscar Barambones, Jose Maria Gonzalez de Durana (Universidad del Pais Vasco). Kremers, E., Lewald, N. IASTED EuroPES 2009, Palma de Mallorca, Spain, September 7 – 9. (2009).

This paper presents an agent-based model for simulating wind power systems on multiple time scales. The aim is to generate a flexible model that allows us to simulate the output of a wind farm. The model is developed using multiparadigm modelling, combining different approaches such as agent-based modelling, discrete events and dynamic systems.
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An integrated pedestrian behavior model based on extended decision field theory and social force model Hui Xi, Young-Jun Son (The University of Arizona); Seungho Lee (Samsung Electronics Co. Ltd.). Proceedings of the 2010 Winter Simulation Conference.

The integrated pedestrian simulation model proposed in this paper allows us to develop a more realistic simulation of pedestrian behaviors at a shopping mall. In particular, consideration of vision of each individual allows us to mimic physical and psychological interactions among the people and the environment more realistically. Similarly, consideration of extended Decision Field Theory allowed us to represent human decision deliberation process. In addition, consideration of a rich set of attributes for the environment as well as people has allowed us to mimic a real shopping mall environment closely. The constructed simulation using AnyLogic software was utilized to conduct several experiments on performance of the mall and scalability of the proposed model.
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Business is a field for experiments. But it’s best to run them on simulation models Timofey Popkov.

Modeling allows you to decrease implementation costs and risks while still in the planning stage. It can also be the best way to optimize existing processes.
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Toward Simulation-Based Real-Time Decision-Support Systems for Emergency Departments Yariv N. Marmor, Segev Wasserkrug, Avraham Shtub. 2009 Winter Simulation Conference (WSC’09), December 13-16, Austin, TX, USA

Emergency Departments (EDs) require advanced support systems for monitoring and controlling their processes: clinical, operational, and financial. A prerequisite for such a system is comprehensive operational information (e.g. queueing times, busy resources,…), reliably portraying and predicting ED status as it evolves in time. To this end, simulation comes to the rescue, through a two-step procedure that is hereby proposed for supporting real-time ED control.
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Autonomic Self-Optimization According to Business Objectives Sarel Aiber, Dagan Gilat, Ariel Landau, Natalia Razinkov, Aviad Sela, and Segev Wasserkrug. International Conference on Autonomic Computing (ICAC'04), May 17 - 18, 2004, New York, New York, USA

Current IT related optimization efforts focus on optimizing IT level metrics such as response times, availability, etc. What the business requires is that such IT optimization be carried out so as to optimize business objectives. Such optimization is not a one-time effort as there may be significant changes, (e.g. server failures, sudden increase in the number of users) that may render any existing policy sub-optimal. Such optimization can be led in AnyLogic.
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