ブログ

Drones, are developing rapidly; their capabilities are increasing and the costs reducing. Their increased use will lift the UK GDP by 2% according to a PwC report. Certainly, they hold great promise, reducing delivery times and cost, as Amazon is exploring, and even have the potential to revolutionize commuting — EHang’s Air Taxi or Uber’s Elevate.

Mosimtec is supporting drone/UAV network deployment through simulation. By exploring operational constraints in a virtual environment, it is possible to evaluate variables such as scheduling, maintenance, fleet size, and charging times. Review and video...

Simulation modeling helped develop an efficient and future proof supply chain for Cooper Enterprises.

Lowering costs for development and implementation, see how simulation modeling works for Cooper Enterprises...

UDES is designed for teaching the complex nature of city interactions, and also a method for representing them – agent based simulation.

It is an excellent example model, accessible to all, with both interactive and customizable elements. Let’s take a closer look…

Get inside the model! In this post, we will look at the technical features of the example Border Checkpoint model: what it consists of, how it works, and what methods were used in its development.

Learn tips and tricks as you go through the model step by step with our expert...

New releases of AnyLogic come with new example models. These help newcomers understand simulations and experienced users to learn about AnyLogic’s advanced capabilities.

New to AnyLogic is our Border Checkpoint model. It is based on the same principles as classical queueing systems, such as those found in banks, shops, and medical centers.

In this post, we show how to model and analyze a variety of these business problems using the new border crossing model.

Fruit of the Loom (FOTL), one of the largest US apparel manufacturers was expanding its product line in early 2014 and faced the decision to add a new distribution center (DC) or to redistribute products to a pre-existing DC. To identify the benefits of each option in terms of cost and supply chain optimization, Fruit of the Loom required greater visualization than typical supply chain management tools could offer.

A smart bike sharing system can provide fast and easy access to public transportation where short trips are common for a large portion of the population. Urban planning officials in the City of Leon, Guanajuato, Mexico believe the socioeconomic conditions along with its societies adherence to this mode of transportation combined with the urban trace and physical conditions encourage the adoption of a bike sharing system. The City of Leon contracted Karla Margarita Gamez Pérez, Eleazar Puente Rivera, and her team from The University of Monterrey to research the possibility of a bike sharing system prior to implementation. Karla’s team chose AnyLogic Software for simulation modeling to carry out the design and dimensioning of the system.

In public transport, bus bunching refers to a group of two or more transit vehicles (such as buses or trains), which were scheduled to be evenly spaced running along the same route, instead running in the same location at the same time, according to Wikipedia. Dave Sprogis, Volunteer Software Developer, and Data Analyst in Watertown, MA noticed a constant complaint from residents about bus service provided by the MBTA. On a route that advertises a bus “every 10 minutes or less” during rush hour, waits were frequently more than 30 minutes, sometimes an hour! As you probably assume, buses do not start out bunched — they start out evenly spaced according to the schedule that deploys them. However, as the buses run the route, some run a little faster while others run a little slower. There is variability in traffic lights, pedestrian crossings, numbers of passengers loading and unloading, or even differences in driver pace.

Over ninety percent of the world’s trade containerized, and in the Port of Hamburg in Germany over nine million containers are transshipped every year. Till now the early provision of information for both the estimated time of arrival (ETA) of vessels and containers is not established. Containers are offloaded and stored at terminals, and then they are usually sent by ground transportation to their further destinations. This hinterland part of the supply chain can often become a bottleneck because if a deep-sea vessel gets delayed, it can complicate further shipment processes. Furthermore, the terminal has no information about the hinterland mode selected or the time of off-loading a certain container (first or last).

While the extensive rail library was a key reason that CSX chose AnyLogic as its general purpose simulation tool for the Network Modeling, Operations Research, and Process Excellence groups, the other libraries and methods have added significant value as well. In fact, the first major project where AnyLogic was used did not utilize the rail library. After reviewing the problem in more detail, a discrete-event simulation model was built to help managers studying train throughput. The model simulated the demand of empty trains from five coal mines, as well as the fulfillment of the demand. A supply-chain-like network model was created, which implemented logic to depict the demand, supply and staging of empty trains. The trains were modeled as moving entities across the network. By varying values of relevant parameters, users can infer the impacts of different factors to the train throughput (i.e. siding staging capacity and loading speeds at the coal mines). The model provides a way for decision makers to gain insight into the system to help identify the maximum possible throughput. The objective was to identify the best operational/capital strategy to handle the increased business.