Discrete_Event_Simulation

Discrete event simulation!!! I chose to do a search through LexisNexis Academic and found an interesting article. It is called Discrete-Event Simulation Guides Pipeline Logistics. It starts out by mentioning the four contributing authors to the article. In continuing, the reader gets some quick background information on discrete-event simulation and a couple kinds of pipelines. The authors mention two specific pipelines: refined products pipelines and multiproduct pipelines. Next in line comes a short discussion on pipeline scheduling. According to the article, input and delivery are of the utmost importance within pipeline scheduling. Interface costs, energy costs, and maintenance costs can all be reduced, respectively, by finding optimal product input sequences and lot sizes, by finding optimal ways to reduce pipeline stoppages, and by finding optimal solutions regarding the pump switches. This is then followed by various formulations, assumptions, and approaches by the authors and previous sources in relation to optimizing pipeline scheduling. This section also contains the sentence, “The model includes binary variables to account for seasonal energy costs and avoid pumping operations during high-cost periods.” This sentence just struck me as fitting and apropos because, as of recently, we have discussed binary variables within our class setting. The next heading, simulation, brings us to the third portion of the article. It opens up speaking about previous simulation models and the current model presented by the current authors. The two former models consist of a simulation one for the scheduling of injection and stripping operations in a real-world pipeline network, and the other was a hybrid one combining a “tabu search” with a discrete event simulation that addressed a real world multiproduct pipeline scheduling problem. The current model that is introduced in this article is a discrete event simulation one, and it is specifically for a trunk pipeline that transports refined products from a single origin to multiple distribution terminals in segregated or fungible mode. We are then led into the example section, where the problem is set up. After the example section, we encounter the segment on the hierarchical solution. This requires two stages. The first stage involves generating the input schedule through the optimization module, and the second stage involves developing a detailed delivery schedule based on the information provided by the optimization. The discrete event simulation definitely assists in figuring out these two stages as well as figuring out a variety of other factors and features. The simulator allows the user or users to actually see the dynamics of a pipeline system over time. This is literally done through an animation interface. Additionally, under the hierarchical solution segment, there were two more items that I found to be noteworthy. The first was the phrase “at terminal j covered by batch i during pumping run k.” This little phrase just caught my eye because in class once again, as of recently, when we are setting up our decision variables, we deal with such wording and lettering as we see right here. Secondly, the simulation modeling seems to be very flexible. Different elements and rules can be added or deleted or simply changed around. I thought that was fascinating how the authors could do that. Furthermore, the reader subsequently comes across four more portions of the paper: the problem statement, the major assumptions, the objective function, and lastly, the model structure with a briefing on simulation blocks. In regards to the problem statement and the major assumptions, this includes a list of definitions and statements that help clarify and effectively tackle the pipeline issues at hand. The objective function speaks of pipeline stoppages as a main topic, mentioning the main cost of stoppage comes from the lost energy of fluid momentum and with these stoppages, the increased cost of maintenance can also be brought forth. Finally, there is the model structure. It communicates to the reader the vast network of a refined products pipeline. There are many key points, crucial sequences, and certain timed events that all have to go according to schedule and be planned appropriately. Technically, whatever is in these pipelines could be idle, could just be entering into the pipeline, could be exiting out of the pipeline, or could possibly be transferring to a second or third pipeline. I did not realize how modern pipeline technology could be so advanced, complicated, and innovative at the same time. It was nice to learn about the material presented in this article.