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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Pipe Spool Fabrication Simulation Model Labban, R., Abourizk, S., Haddad, Z, El-Sersy, A., I3M Conference 2013, Athens

When dealing with larger and more complex construction operations, which are more difficult to manage using traditional project management tools, computer simulation methods have shown to be effective in designing and analyzing construction processes, regardless of the complexity or size. A simulation model can be built to describe the construction activities of a scope of work ranging from large, complex industrial projects to a simple room of a small building. Using simulation, engineers can test out different construction scenarios, estimate resource utilization and find bottlenecks, and forecast time and cost requirements without having to go to site.
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Simulation of On-Shore Wind Farm Construction Process in Lebanon E. Zankoul and H. Khoury, The 31st International Symposium on Automation and Robotics in Construction and Mining (ISARC 2014)

The solution to the problem of electricity supply shortage in remote regions of Lebanon is described in detail using a discrete-event simulation model of a constructinon process developed in AnyLogic. The work illustrates the different construction stages from rough grading, access roads construction, foundation and electrical works, to wind tower assembly and erection. The whole process is then optimized to mainly minimize the project duration.
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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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Development of an Agent-Based Model for the Secondary Threat Resulting from a Ballistic Impact Event Matthew J. Bova, Frank W. Ciarallo, Raymond R. Hill

The process by which a high-velocity impact event leads to fire ignition onboard military vehicles is complex, influenced by the interaction of heated debris fragments and fuel spurting from ruptured tanks. An assessment of the risk of such a fire begins with a complete characterization of the secondary threat resulting from the impact, including debris fragment sizes, states of motion, and thermal properties. In the aircraft survivability community, there is a need for an analytical tool to model this complete threat.
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Comparison between Individual-based and Aggregate Models in the context of Tuberculosis Transmission Tian, Y. and Osgood, N., Proceedings, The 29 th International conference of the System Dynamics Society. July 2011, Washington, D.C.

The desire to better understand the transmission of infectious disease in the real world has motivated the representation of epidemic diffusion in the context of quantitative simulation. In recent decades, both individual-based (such as Agent-Based) models and aggregate models (such as System Dynamics) are widely used in epidemiological modeling. This paper compares the difference between system dynamics models and agent-based models in the context of Tuberculosis (TB) transmission, considering smoking as a risk factor.
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Representing Progression and Interactions of Comorbidities in Aggregate and Individual-Based Systems Models Osgood, N. Proceedings, The 27th International Conference of the System Dynamics Society, July 2009, Albuquerque

Healthcare simulation models have attracted significant offered important insights in to health policy selection. More complete accounting for the cost and health implications of upstream interventions is hindered by the need to consider impact on, and interactions between, multiple comorbidities. Within this paper, we explore several distinct approaches for representing comorbidities, some of them at the aggregate level, and some of them at the individual level. All of these representations have the virtue of being declarative, in that they allow the user to focus on what is to be characterized, rather than how it is to be implemented. Our exploration suggests that while several aggregate representations of comorbidities are possible, they suffer from a variety of shortcomings, ranging from low fidelity to combinatorial blowup. While individual-level representations impose a heavy performance load, greater difficulties in calibration and less rapid analysis, such representations do offer greater transparency, modifiability, scalability, and modularity, and ease of representing transmission and influence networks. With much to recommend each approach, further research is needed to shed additional light on the tradeoffs and identify situations where one representation is preferable to another.
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SILVER: Software in Support of the System Dynamics Modeling Process Nathaniel Osgood, Proceedings, The 27th International Conference of the System Dynamics Society, July 2009, Albuquerque

While the System Dynamics modeling process can yield invaluable high level insights, it gives rise to a tremendous amount of detail complexity. In the course of their work, modelers must track successive model versions, the motivation for and assumptions underlying particular “what if” scenarios, and the implicit relationships between scenarios, model versions and various external artifacts such as spreadsheets, symbolic mathematics calculations, and external documentation.
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Logistics Simulation and Optimization for Managing Disaster Responses F. Barahona, M. Ettl, M. Petrik, P.M. Rimshnick, IBM T.J. Watson Research Center, Proceedings of the 2013 Winter Simulation Conference

Catastrophic events such as hurricanes, earthquakes or floods require emergency responders to rapidly distribute emergency relief supplies to protect the health and lives of victims. In this paper we develop a simulation and optimization framework for managing the logistics of distributing relief supplies in a multi-tier supply network. The simulation model captures optimized stocking of relief supplies, distribution operations at federal or state-operated staging facilities, demand uncertainty, and the dynamic progression of disaster response operations. We apply robust optimization techniques to develop optimized stocking policies and dispatch of relief supplies between staging facilities and points of distribution. The simulation framework accommodates a wide range of disaster scenarios and stressors, and helps assess the efficacy of response plans and policies for better disaster response.
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Discrete Event Simulation Model of Asphalt Paving Operations Ramzi Labban, Simaan AbouRizk et al., Proceedings of the 2013 Winter Simulation Conference

Although research into simulation of construction continues to advance and thrive in the academic world, application of simulation in the construction industry remains limited. Stakeholders on construction projects have yet to adopt simulation as their default tool of choice for managing large complex projects, instead of traditional techniques, which are often inadequate. This paper describes the building of an asphalt paving simulator, as an example of the rigor and effort required in developing construction simulation models, and then briefly describes an alternative model building method currently being researched which may potentially make it easier and faster for stakeholders to quickly build construction simulation models.
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