Client: Carrollton Concentra
Team: Daniel Olivares, Beverly Ross, Devin Kyles
Faculty Advisor: Dr. Siems
Year: 2011
Documents: Final Report, Presentation
Concentra presented the problem of cross-staffing some of its employees throughout its centers. The problem addresses a potential decision of staffing methods of which the options were to staff to the market or create a cross-staffing model. These decisions relied upon the variability of patient visits among the centers and the ability to schedule based on future forecasted patient visits. Ultimately, the question was to find if there is an opportunity to staff across all centers or must it be dynamically adjusted based on forecasting by center. A solution to this problem would potentially decrease patient wait times and turnaround times (a patient’s check-in time to checkout time), idle times in which staff members are not performing any duties, and times in which centers experience a heavier traffic flow. Read more…
Client: Texas Plaza, Prof. Peiser
Faculty advisor: Dr. Barr
Year: 1982
Documents: Final report (PDF)
Appeared in different form as a journal cover article. R. Peiser and Scot Andrus, Phasing of Income-Producing Real Estate, Interfaces 13:5 (1983) 1-9.
Integer programming techniques were used to determine the order in which to build office buildings and when to put the space on the market for a seven-building, 90-acre, mixed-use real estate project in Texas. The output of the optimization provided development managers with the schedule for opening each building, the amount of space to be leased each year in each building, and the annual cash flows to the owner.
Client: Austin Commercial
Team: David Walls
Faculty advisor: Dr. Barr Year: 2004
Documents: Final report (PDF)
Austin Commercial is a prominent Texas-based construction firm specializing in large-scale projects, including the American Airlines Center, D/FW Airport, and other Dallas landmarks. In recent years, a major challenge has emerged: how to manage the large number of change orders in their construction projects. The focus of this work is to quantify these changes and calculate their impacts on the construction’s cost and schedule. Read more…
Client: Federal Reserve Bank of Dallas
Team: Alex Grosjean, Brianna Bauer
Faculty Advisor: Dr. Siems
Year: 2011
Documents: Final Report, Presentation
Every month, the Treasury sends out roughly ten million physical checks for Social Security payments and other benefits. On average, it costs them about $1 apiece to send these checks via surface mail. As a cost saving method, the Treasury is now requiring these recipients to use direct-deposit methods, and will eventually cease to send out physical checks.
This is where the Federal Reserve’s GoDirect program comes in. GoDirect is both a call center and a website which helps the recipients switch over to direct deposits, which only cost about 9 cents per person. The return on investment for this project is expected to be ten years. The Call Center wishes to optimize the schedule of employees to handle these incoming calls; thus our goal is to design a model to minimize the cost associated with the call center. Read more…
Client: Lockheed Martin Missiles and Fire Control
Team: Stephen Beckert, Brandon Joslin, Pierce, Meier
Faculty Advisor: Dr. Barr
Year: 2010
Documents: Final Report, Presentation
Lockheed Martin presented us with a project more exciting than we could ever imagine: aiding the research into ways to model the effects of an Electromagnetic Pulse (EMP). EMP is extremely devastating and can be caused by both natural and man-made events. EMP primarily affects electronic devices, rendering them useless or destroyed. Since the United States is heavily dependent on electronic interfaces, we are extremely vulnerable to this effect. In addition to this vulnerability to the EMP effect, the United States has a complex system of connected critical infrastructures that have not been studied as interrelated systems. This presents a major problem, how can one forecast the possible failures of such a massive complex system? Read more…
Categories: Computational probability, Dallas-Ft. Worth Area, Defense, Energy, Final report, Forecasting, Government, Integer programming, Nonlinear programming, Operations, Planning, Presentation, Reliability analysis, Scheduling, Simulation, United States, Video Tags:
Client: Methodist Dallas Medical Center
Team: Kyle Chester, Kristin Evanto, and Emily Gray
Faculty Advisor: Dr. Barr
Year: 2010
Documents: Final Report, Presentation
A “hub” of activity at MDMC is the Outpatient Services department. Outpatient Services exists to serve the needs of physicians and surgeons alike with routine x-rays, blood draws to test for Tuberculosis or other ailments, or diagnostics to assess patient health. Many patients who come to Outpatient Services are preparing for surgery and thus need to undergo preliminary screens such as blood draws and EKGs.
The focus of this project is the observation and analysis of the administrative and technical operations within the laboratory component of Outpatient Services. Outpatient Services aims to reduce its patient wait times throughout the entire duration of a patient’s stay in Outpatient Services. Management has expressed a desire to reduce patient wait times such that 95% of all patients wait less than 15 minutes for the Outpatient laboratory department. Read more…
Team: Robert Walters, Donnet Phillips
Faculty advisor: Dr. Barr Year: 1986
Documents: Final report (PDF)
There are many optimization procedures and algorithms that can be implemented for delivery operations. The thrust of this paper concerns the following topics and their relavance to delivery vehicles: equipment replacement, truck utilization and optimization, and efficient routing practices. Read more…
Client: Capstone Asset Management Co.
Team: Mallory Harrison, Natalie Jaroski
Faculty advisor: Dr. Barr Year: 2010
Documents: Final report (PDF), Presentation (PDF)
Capstone is a privately owned investment advisory firm in Houston, TX that offers privately managed accounts to achieve client’s financial objectives. They currently manage over $3.8 billion in assets for about 3,000 different clients. They provide products and services through three distribution channels: brokers/advisors, institutions/corporations, and high-net-worth individuals. Revenues are generated by marginal product fees associated with assets under management allocated by product.
Capstone has in place a detailed budgeting process but desires to expand the process to include financial modeling to measure profitability by product. Our goal for this project is to develop a model that would calculate existing profitability on assets under management by product. Our second goal is to develop an optimization model that takes into account the revenues and expenses associated with sales of existing products versus the revenues and expenses associated with the development of new products. The final output of the optimization model is to identify the most profitable mix for new product sales. Read more…
Categories: Final report, Finance, Forecasting, Houston, Marketing, Optimization, Planning, Presentation, Scheduling, Simulation, Texas, United States, Video Tags:
Client: Lennox Industries
Team: Diana Batten, Maddie Kamp
Faculty Advisor: Dr. Siems
Year: 2011
Documents: Final Report, Presentation
Lennox Industries is a residential and commercial heating and air-conditioning company with a 13-15% market share in about 80 countries. Lennox is unique in that they operate as both the manufacturer and distributor of their products selling directly to their customers, typically contractors.
This project identified correlations between customers’ buying patterns and their attrition, or loss of their business. Based on transaction-level data of 4,500 customers over a three-year period, an early-warning model was developed to signal the potential loss of a customer and enable Lennox to act preemptively. The analytics were based on a ranking procedure based on key indicators and a Markov chain analysis with categorical transition probabilities derived from historical data. With this model encapsulated in spreadsheet form with the ability to customize the analysis geographically and seasonally, the results give Lennox management a new tool to maintain their current customers and evaluate new markets.
Client: Arlington Texas Police Department
Team: Ron Andrews, Blake Robinson
Faculty Advisor: Dr. Siems
Year: 2011
Documents: Final Report, Presentation
The Arlington Police Department is responsible for policing the city of Arlington to achieve a safer community. The policing of the city is divided roughly into four main areas (north, south, east, and west) with each respective area possessing its own police station. The Arlington Police Department requested insight into the placement of the police stations to see if they were effectively located to process the level one crimes that originate from each main area. If a main area was not adequately covered, areas could be hypothetically redrawn to accommodate effective policing.
Our method of analysis included the use of in-depth data analysis and a pure network model that had the potential to take into consideration Euclidean distances, time schedules, crime severity and political issues. Our findings indicated that the placement of police stations given current population levels were placed reasonably close to where our model suggested they should be placed. It was also discovered that complex issues such as political issues and crime severity are hard to quantify within a model given due to the ambiguous nature of the data.
