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Archive for the ‘Optimization’ Category

Optimizing Sales Force Levels for Gamesa

May 15th, 2012 No comments

Client: Frito Laygamesa-logo-6281d3ca58-seeklogocom
Team: Rodrigo Cantu, Sergio Hueck, Rafael Virzi
Faculty Advisor: Dr. Barr
Year: 2012
Documents: Presentation, Report, Video

Gamesa, a subsidiary of Frito-Lay, is a Mexican Cookie company that sells its product in many different countries, including the United States. Their products, which includes different types of cookies and crackers, are targeted to the Mexican population. The company’s United States sales force consists of 38 representatives in 16 different regions, organized by their different routes to market, location of warehouses, and population density. Today, they dominate the U.s. Hispanic cookie market occupying 50 percent of the market.

The problem we address for Gamesa is: should they should deploy more sales representatives and, if so, where would their optimal locations be? With the current economic recession and the entering of Gamesa’s main competitor, Bimbo, sales have been dropping in the different regions. This resulted in Gamesa asking themselves if they needed a bigger sales force. They also wanted to know what regions could be good to add representatives in the future depending on the migration of the population or the strategy of the competition. Read more…

Optimizing Product Transportation from Hispanic Markets

May 15th, 2012 No comments

Client: Frito Laygamesa__2006_-logo-cb8481d8e4-seeklogocom
Team: Javier Gonzalez, Fernando Sada, Marcelo Sada
Faculty Advisor: Dr. Siems
Year: 2011
Documents: Final Report, Presentation

In order to satisfy the large Hispanic market in the United States, Frito Lay imports products manufactured in Mexico by Gamesa, a sister company to Frito Lay due to the fact that they are both owned by PepsiCo. Gamesa has plants all across Mexico, having the main ones located in Celaya, Vallejo, Obregon and Monterrey. In the past, all products being imported into the U.S were produced in Obregon, a city in Northwestern Mexico. As of today, the Hispanic population has dispersed all across the country, increasing Gamesa’s market to a large portion of it. Gamesa’s products are now being distributed all the way from California, to Texas, and onto the East Coast and Midwest. Imports have increased so much that in order to satisfy the demand, Gamesa has started producing all across Mexico for exports. Read more…

Rental Engine Check-in and Repair Optimization Scheduling

March 7th, 2012 No comments

Client: Pratt & Whitney Engine Servicesprattwhitney
Team:  Michael DeVore
Faculty advisor: Barr   Year: 2004
Documents: Final report (Word)

The Pratt and Whitney Addison Service Center is a unique situation involving rental engines and their repair.  These engines are delivered by a 3rd party carrier and must be checked over and repaired if necessary.  At that point the engine must be sent back out to either the customer who rented it or to another intermediate step.  The Addison, TX Service Center Manager requested help in optimizing the employee’s time spent on these rental engines.  He wanted to know what could be done to improve Service Center response time and maximize output.  Read more…

Optimal Phasing of the Opening of Buildings in an Office Complex

March 7th, 2012 No comments

Client: Texas Plaza, Prof. Peisertxplaza
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.

Call Center Personnel Scheduling

February 1st, 2012 No comments

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…

Lockheed Martin: Electromagnetic Pulse Modeling

January 31st, 2012 No comments

EMP blast effects

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…

Optimization Models for a Delivery Truck Environment

January 20th, 2012 No comments

long-haul-delivery-trucks-722198
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…

Financial Product Mix for Capstone Asset Management

October 31st, 2011 No comments

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…

Arlington Police Crime Coverage Model

October 31st, 2011 No comments

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.

Heelys Order Management: A Reassessment

September 27th, 2010 Comments off

heelys-sneakers-mit-der-rolleClient: Heeling Sports Limited
Team: Gustavo Carrere and Marcus Klintmalm
Faculty Advisor:  Dr. Siems
Year: 2005
Documents: Final Report (PDF)

The Heeling Sports Limited is a Dallas-based footwear designer, manufacturer and distributor. The Company’s mission is to generate new and exciting footwear utilizing contemporary and progressive styles with comfort-enhancing performance features. To generate new footwear style HSL will introduce one product per year through acquisition or in-house development.

Extensive interviews and observation lead us to several bottlenecks in the order process. Most often these bottlenecks concerned procedure rather than anything else. There are many simple, no-cost options to optimizing the Heelys order process. Read more…