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Improving Intersection Efficiency with Connected Vehicle Technology


Improving Intersection Efficiency with Connected Vehicle Technology

Traffic control strategies at intersections have evolved through applying advanced control technologies during recent decades, especially for signalized intersections around urban areas. Now, with emerging connected vehicle technology there is a renewed potential to improve the overall efficiency and safety conditions at intersections. A group from the Department of Civil and Environmental Engineering at The University of Tennessee, Knoxville conducted a study of the relationship between average system delay and average queue length for traffic approaching signalized intersections. The team utilized data from the City of Detroit collected in a field test during the 2014 Intelligent Transportation Systems World Congress.

Senior Executive Decision Support Tool at USAA


Senior Executive Decision Support Tool at USAA

The United Services Automobile Association (USAA) is a Fortune 500 Company offering diversified financial services and insurance to people and families that serve or have served in the United States Military. With nearly 12 million members and various services, it is imperative that USAA’s business initiatives with strategic objectives of the enterprise are aligned. To accomplish this alignment, USAA combines advanced analytics, simulation methods, and enterprise architecture concepts to create dynamic and systemic models of the enterprise. A major catalyst in these efforts is Dr. Bipin Chadha, Data Scientist at USAA who has developed several decision support models for strategic planning, capability roadmaps, operational risk analysis, capacity planning and scheduling, and portfolio optimization.

Lockheed Martin - Improving Military Aircraft Turnaround Process


Lockheed Martin - Improving Military Aircraft Turnaround Process

The military aircraft maintenance turnaround process is highly complex and includes multiple interacting and parallel workflows between humans and machines. Lockheed Martin, one of the largest companies in the aerospace, defense, security, and technologies industry sought to improve decision-making in regards to the complete turnaround process and to identify process changes that could be implemented to reduce turnaround time. There are two distinct features unique to the project. One being the use of AnyLogic to model people, machines and workstations, and how they interact, which identified previously unknown workflow peculiarities. The second, a portable Android tablet application developed and tested by the team for workflow authoring and data collection that provided the input data to the process simulation model.

Dimensioning of Bike Sharing Systems in the City of Leon, Guanajuato, MX


Dimensioning of Bike Sharing Systems in the City of Leon, Guanajuato, MX

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.

Beyond Marketing-Mix Models


Beyond Marketing-Mix Models

A multi-national pharmaceutical company recently launched a new non-generic drug. Since the company already owned the leading non-generic drug in that market, cannibalization was a concern. The goal was to create market share for the new drug, while maintaining or increasing market share for the well-established drug by modifying types of promotional spend. Traditionally, the Analytics Department would employ a Marketing-Mix Model (MMM) to determine the impact of promotional spend, but the company was looking for further insight into the mechanics behind the MMM. After exploring multiple options, they determined agent-based modeling, and ultimately AnyLogic would allow for the greatest flexibility and visualization.

Using Simulation to Tackle Added Constraints on a Complex Earthmoving and Construction Project


Using Simulation to Tackle Added Constraints on a Complex Earthmoving and Construction Project

Consolidated Contractors Company (CCC) is the largest construction company in the Middle East and ranks #18 internationally. Its portfolio includes oil and gas plants, refineries and petrochemical facilities, pipelines, power and desalination plants, light industries, water and sewage treatment plants, airports and seaports, heavy civil works, dams, reservoirs and distribution systems, road networks and skyscrapers. CCT International (CCT) is the primary technology provider for CCC since 1998. CCT also develops and markets solutions for the construction industry with clients all over the world.

Road Traffic Simulation for City Planning: New AnyLogic Library in Action!


Road Traffic Simulation for City Planning: New AnyLogic Library in Action!

When planning new transfer hubs, developers need to verify the stations would provide expected passenger capacity, while city authorities have to learn how building a station would affect traffic in the area and public transfer load. Simulation modeling is a perfect instrument for solving such challenges. We covered, in a past blog, one of the models built for the Moscow Ring Railway project, passenger flow simulation at Cherkizovo transfer hub, where a station layout was tested at peak passenger loads. The project we are going to discuss today is another model of Moscow public transport system. We will talk about automobile traffic flow research at the transport hub of Volokolamskaya, done by ITS Consulting.

Warehouse Modeling and Optimization Saves Millions for Cardinal Health


Warehouse Modeling and Optimization Saves Millions for Cardinal Health

Being #26 in last years’ Fortune 500 list, Cardinal Health is a billion dollar pharmaceutical distribution and logistics company. Its clients are hospitals, pharmacies, physicians, and individual consumers. They face a multitude of typical distribution warehouse challenges that are further complicated by the nature of pharmaceutical products, which are smaller in size, consumable, expensive, and could be life critical. Company’s warehouses have narrow passages, and workers operate big multilevel trolleys. That increases the probability of employees’ mistakes and makes these mistakes costly.

Automated Production Line Optimization: Case Study


Automated Production Line Optimization: Case Study

Centrotherm Photovoltaics AG is a global supplier of technology and equipment for the photovoltaics, semiconductor, and microelectronics industries. The company needed to identify the best configuration of the automated production line and factory, to minimize costs and maximize throughput and reliability. Throughput and equipment utilization rate metrics were utilized to compare alternatives. Centrotherm needed to avoid possible bottlenecks in the material flow and optimize in-factory logistics. Also, management required taking into account casualties and stochasticity, for instance, the probability of scrap or how the factory would operate in case of equipment breakdowns.

IBM Project Published in Journal of Medical Systems and Recognized by the United States House of Representatives


IBM Project Published in Journal of Medical Systems and Recognized by the United States House of Representatives

At the AnyLogic Conference 2014, Kyle Johnson, Global Business Services in Advanced Analytics and Optimization at IBM partnered with Otsuka Pharmaceuticals, presented a “Multi-Agent-Based Simulation of a Complex Ecosystem of Mental Health Care.” To date, the research paper was published in the Journal of Medical Systems and received the attention of the United States House of Representatives [1]. The project revolves around the housing cycle of the United State’s Severely and Persistently Mentally Ill (SPMI). An SPMI patient defines someone with a diagnosis of Schizophrenia, Bipolar Disorder, or Major Depressive Disorder, and this group constitutes about 1.7% of the US population. To better understand the condition and possible improvements, IBM Global Research and Otsuka Pharmaceuticals used an agent-based approach to model the SPMI living situations over the second half of the 20th century.