Articles

Agent-Based Modeling Framework for Simulation of Complex Adaptive Mechanisms Underlying Household Water Conservation Technology Adoption


Using new technologies to maintain, construct, and reuse naturally created products like asphalt, soils, and water can reserve the environment. The objective of this study was to specify and model the behavior of households regarding the installation of water conservation technology and evaluate strategies that could potentially increase water conservation technology adoption at the household level. In particular, this study created an agent-based modeling framework in order to understand various factors and dynamic behaviors affecting the adoption of water conservation technology by households. The model captures various demographic characteristics, household attributes, social network influence, and pricing policies; and then evaluates their influence simultaneously on household decisions in adoption of water conservation technology. The application of the proposed simulation model was demonstrated in a case study of the City of Miami Beach. The simulation results identified the intersectional effects of various factors in household water conservation technology adoption and also investigated the scenario landscape of the adoptions that can inform policy formulation and planning.

The History of Simulation Modeling


During the past half-century simulation has advanced as a tool of choice for operational systems analysis. The advances in technology have stimulated new products and new environments without software standards or methodological commonality. Each new simulation language or product offers its own unique set of features and capabilities. Yet these simulation products are the evolution of research, development, and application. In this paper we interpret the historical development of simulation modeling. In our view simulation modeling is that part of the simulation problem-solving process that focuses on the development of the model. It is the interpretation of a real production (or service) problem in terms of a simulation language capable of performing a simulation of that real-world process. While “interpretation” is in the “eyes of the beholder” (namely us) there are some historical viewpoints and methods that influence the design of the simulation model.

Exploring Cannulation Process in Chemotherapy through a Computer Simulation


The aim of this study is twofold. Firstly, to demonstrate how combining computer simulation, data from multiple data sources, and statistical methods, can extend the understanding of the issues associated with process modelling and analysis in healthcare environment, and therefore contribute to improvements in resource utilisation and safety in hospitals. Secondly, to provide simple re-useable methodology for cross-validation of multiple data-sources such as interviews, hospital IT data management systems and simulation results. The insights from this study are threefold. Firstly, the accuracy of the estimates of duration of cannulation obtained through the interviews with the nurses and the chemotherapy unit manager is very high. Secondly, although the duration estimates were precise, the process descriptions obtained through interviews with nurses were oversimplified or incomplete and therefore did not realistically reflect complexity of a medical process with a significant number of relatively rarely occurring exceptions. Thirdly, by combining multiple data-sources it is possible to reduce costs associated with observation as a most expensive data-capturing approach. A detailed exposure of the methodology including step-by-step description is provided to facilitate conducting similar research in hospitals in the future.

Signal Phase Timing Impact on Traffic Delay and Queue Length-a Intersection Case Study


Traditional intersection traffic signal control strategy is pre-determined signal with certain phase timing length for each circle. Studies focusing on adaptive traffic signal strategy have somewhat achieved the goal of reducing traffic system delay to some extent. However, few of them capture the benefit of using the queue length as the criteria under the connected vehicle environment, and this paper focuses on firstly identifying the potential saving of average system delay with agent-based simulation modeling, and secondly finding out the relationship between average system delay and average queue length for traffic approaching the signalized intersections. Through applying the agent-based simulation modeling approach in AnyLogic, findings show that average system delay could be reduced using optimized parameters (e.g. arrival rate, signal phase length, etc.), specifically, 5.29% saving of total average system time, 4%-28% traffic queue reduction for different traffic lanes, and a positive relationship between average system de-lay and the average traffic queue length is detected.

Simulation-based Framework for Teaching Methods in Logisitc and Production Planning


Uncertainty in planning tasks such as processing times, set up times, customer required lead times, due dates, time to failure, time to repair and the complexity in terms of product variety, outsourcing, short lead times, low inventory levels, low costs, high utilization are major hurdles for planning logistic and production processes. This poster introduces a business game for methods in logistics, production planning, procurement, production, distribution and sales tasks. Basic methods such as MRP, CONWIP, Kanban, reorder policies, dispatching rules, basic demand forecasting methods, MPS are implemented in the game. Due to the generic environment additional methods can be implemented efficiently. Attention has also been paid to a didactic learning concept. A web based platform has been developed where presentation and videos will support the learning effort of the gamers. Online pre-test are included to examine the current skills.

Simulation testbed for the analysis of beneficial business strategies for the airbus A350 production ramp-up


The production ramp-up of new aircraft is characterized by high complexity and planning and control chal-lenges caused by complex product design, supply chain and production processes. In the past, this resulted in significant delays and increased costs of the production ramp-up. Novel business strategies and planning and scheduling technologies promise better production control and risk mitigation during the ramp-up phase. The European research project ARUM has developed those business strategies and a new distributed decision support solution based on knowledge processing technologies. A simulation testbed was used to identify the most beneficial business strategies and to evaluate linked control strategies for the industrial use case of the Airbus A350 production ramp-up. This paper discusses the potential of simulations for the business strategy definition and for the validation of linked control strategies from the industrial end-user perspective.

Auction policy analysis: an agent-based simulation optimization model of grain market


National grain reserve is important in terms of responding to disasters and the unbalance between supply and demand in many countries. In China, the government supplements grain supply through online auctions. This study focuses on the auction policy of national grain reserve. We develop an agent-based simulation model of China’s wheat market with detail descriptions of different agents, including national grain reserve, grain trading enterprises and grain processing enterprises. Based on this model, the Optimal Computing Budget Allocation (OCBA) simulation optimization method is adopted to analyze the characteristics of optimal decision variables under different scenarios, with an objective to minimize the fluctuation of wheat price. We obtain some insights about operations of national grain reserve. As the first agent-based simulation model about national grain reserve and grain market, this model can be widely used in agricultural economics, and can provide policy supports to the government.

Discrete event simulation on the Macintosh for business students - aGPSS and alternatives


The paper first discusses the importance of discrete event simulation (DES) in the business school curriculum. It next notes how small Macintosh lap tops have become increasingly popular among business students. We next discuss what DES software is available on the Mac, first directly, then indirectly by running DES software for Windows in some way on the Mac. Noting that there is not much simple DES software on the Mac, but yet a great demand for such software from many business students, we turn to the transfer of one pedagogical software system, aGPSS, from Windows to the Mac. We here first give a brief historic background of aGPSS. Next we discuss some of the problems encountered when transferring aGPSS to the Mac. The paper ends with a brief discussion of some pedagogical aspects of using aGPSS on the Mac in the teaching of basic management science.

High level architecture (HLA) compliant distributed simulation platform for disaster preparedness and response in facility management


By imitating chaotic disaster situations in risk-free settings, disaster-related simulation can be helpful for training of response participation, damage evaluation, and recovery planning. However, each single simulation needs to interact with others because different simulation combinations are required due to numerous disasters and their complex effects on facilities, and diverse response efforts. We therefore developed a distributed simulation platform for disaster response management by using the High Level Architecture (HLA) (IEEE 1516) to promote its future extendibility. With a focus on the facility damage after an earthquake and fire, disaster response simulations—including evacuation, emergency recovery, and restoration—interact with a seismic data feeds, and structural response and building fire simulations. This base platform can provide information on possible damages and response situations to reduce confusions in disaster responses. With the strongest features of HLA, which is reusability and extendibility, additional disaster simulators could be coupled for all-time disaster management.

Simulation of maintenance strategies in mechanized tunneling


Mechanized tunneling is one of the most common methods used for underground constructions for infrastructure systems. Since a tunnel boring machine (TBM) represents a non-redundant single machine system, the efficiency of maintenance work highly impacts the overall project performance. The wear and tear of cutting tools is a critical, but mostly unknown process. To plan the maintenance work of cutting tools efficiently, it is necessary to know the current tool conditions and adapt the planned maintenance strategies to the actual status accordingly. In this paper, an existing theoretical empiric surrogate model to describe cutting tool conditions will be used and implemented as a software component within a process simulation tool that manages TBM steering parameters. Further, different maintenance setups for TBM cutting tools are presented and evaluated. To prove the capability of the presented approach, a case study will show the effects that improved maintenance work can have on project performance.