Agent-Based and Monte Carlo Simulation for Istanbuls Transportation Network - Essay Example

of southampton WORK PART C [Type the document sub AHMAD ALHARBI 29 [As businesses are becoming more complex with time,simulation has gained quite some popularity. Two types of simulation, namely, agent based simulation and Monte Carlo Simulation are discussed in this paper and how they apply to real life situation] Table of Contents Table of Contents 1 Introduction With the businesses growing more complex and science getting more advanced with time, simulation plays a significant role as it allows complex organization to test operations through imitating a model of the system before hand. The main purpose of applying simulation for any project to is to reduce the risk of the problems that the new system may bring about to the entire project and may bring the entire business to a standstill because the new operation was not tested beforehand. For any kind of simulation, a different model has to be developed. There are two such models, namely, Agent based simulation and Monte Carlo simulation. In this paper, an attempt has been made to review to scholarly articles where the above mentioned simulations have been applied in real life situations. For agent based simulation, a case study of non-pharmaceutical strategies to combat influenza has been selected. For Monte Carlo simulation, improving the reliability and performance of the transportation network of Istanbul under earthquake has been selected. The idea is to review the case study to understand the problem faced and how simulation helped solved the issue through its unique characteristics. Agent Based Simulation Agent based simulation is an approach whereby agents are used to note the extent to which the project is a success for a certain kind of simulation. In the paper by Mao, the non-pharmaceutical strategies to combat influenza were considered under agent based simulation. For some time, non-pharmaceutical strategies to combat the impact of influenza have been under consideration and have been studied. One such strategy is the weekend effect that has not been quite so studied. Mao studied how six weekend extension strategies reduce influenza. For this, the researcher extended this strategy by one, two and three days in the city of Buffalo, New York. In order to understand how this impacted the influenza, agent based simulation was used. These agents were taken from Buffalo, New York and they were further categorized into different locations as well as timings. It was assumed that these agents met a variety of people when socializing and travelling and thus could be good agents of carrying and transporting the influenza virus. In order to kick start the study, five agents were introduced in the case study already carrying the influenza virus and thus spread the virus within the state. These agents were asked to resume normal day activities and socialize also so as to create an accurate study (Mao, 2011). The results of the survey showed that when flu was extended to two more days, it is expected to minimize the seasonal influenza’s disease attack rate. With a three day extension, more desirable results were to be found as the spread of the disease is further curtailed. This was because when people limit their interactions with others, the spread of the virus is also limited. This strategy was thus found to be quite practical since individuals can easily take a day off when they have caught the seasonal flu. Such a strategy can be advantageous in countries that do not have access to proper vaccination and pharmaceutical medicines (Mao, 2011). Monte Carlo Simulation – Case Study of Istanbul’s Transportation Network Ordinarily, during natural or man-made disasters, chaos ensues. This makes it difficult to effectively develop a disaster response as transportation is the most impacted area of the disaster. For rescue and relief operations to be carried out effectively, transportation system of water, energy, communication should be effective. In order to deal with this complex issue, the study conducted by Gunnec and Salman, a Monte Carlo simulation algorithm was used. The city of Istanbul was specifically chosen and the response was developed for earthquake risk. Istanbul was chosen as the preferred city since it is believed to be a high earthquake risk area (Gunnec and Salman, 2011). For this paper, the researchers took a network and inspected its performance and reliability in case an earthquake was to occur in Istanbul. Eight different measures were analyzed in the framework of the impact on transportation after the earthquake. It was taken into account that after an earthquake, links of transportation are likely to be down. A set of dependent and independent links were taken into account, where dependent links were identified to be those that had a novel vulnerability-based link dependency structure and the chances of its survival (Gunnec and Salman, 2011). In this framework, it was also assumed that certain links were strong links while others were weak links. These weak links were identified to be those closest to the main earthquake area on the basis of the strength of the bridges. Thus, a polynomial-time algorithm was found to be the most suitable in this scenario ( Gunnec and Salman, 2011).. Under the Monte Carlo simulation algorithm, which was used for difficult computation, it was found that the network’s performance and reliability can be tested with moderate computation time. Monte Carlo simulation algorithm was used because it is difficult for gain accuracy in the same of all-independent cases affecting the transportation network. The conclusions of this study proposed the fact that the algorithms developed in the model can be used for practical purposes (Gunnec and Salman, 2011). Conclusion In this report, two different case studies pertaining to two different simulation methods have been discussed; these methods being Agent Based Simulation and Monte Carlo Simulation. In agent based simulation, agents were used to evaluate the effectiveness of non-pharmaceutical strategy, namely the weekend effect, to combat the issue of influenza. The results of the case study bring promising answers which leads to the conclusion that agent based simulation was quite effective in dealing with this issue. The study concluded that the weekend effect, if extended to three more days, can be quite effective in both limiting and preventing the condition of flu. For the Monte Carlo simulation case study, a case study of the reliability and performance of Istanbul’s transportation network was studied under the stress of a natural disaster, namely earthquake. For this different measures were used and applied to a Monte Carlo simulation which led to promising results. References Gunnec, D, & Salman, S. 2011, 'Assessing the reliability and the expected performance of a network under disaster risk', OR Spectrum, 33, 3, pp. 499-523, Academic Search Premier, EBSCOhost, viewed 14 January 2013. Mao, L., 2011, Agent-based simulation for weekend-extension strategies to mitigate influenza outbreaks, BMC Public Health, 11, pp. 522 Read More