Figure 2: Network Routing Options
Other OR topics requiring mathematical analysis are inventory control (when to reorder material to avoid shortages under demand uncertainty), manufacturing operations (what size of production run will minimize sum of inventory and production setup costs), location planning (where to locate the hub to serve markets with minimal travel distances), and facility layout (how to design airport terminals to minimize walking distances, maximize number of gates, allow for future expansion, and conform to government regulations).
OR analysts can model difficult practical problems and offer valuable solutions and policy guidance for decision-makers. Constraints involving budgets, capital investments, and organizational considerations can make the successful implementation of results as challenging as the development of mathematical models and solution methods.
In general, Operations Research requires use of mathematics to model complex systems, analyze trade-offs between key system variables, identify robust solutions, and develop decision support tools. Students of mathematics can be sure there are plenty of uses for the knowledge and skills they are developing. As the world becomes more complex and more dependent on new technology, mathematics applied to business problems is likely to play an increasingly important role in decision-making in industry.
On a personal note?
All three of us developed an interest in the mathematical sciences early on, and took undergraduate degrees in math, or math and physics. We each got into the field of Operations Research as a result of looking for practical ways to use our math training. Below, we each answer the question: ?How did you decide on a career in math and decide to join GM??
Dennis Blumenfeld: The math courses I liked best were the ones on applied topics. I found Operations Research an especially appealing subject, since it uses basic mathematical principles in clever ways to solve all kinds of complex problems in everyday life ? such as queueing, reliability, scheduling, and optimization. I was intrigued by applications of OR models to traffic flow and congestion, and as a graduate student at University College London I focused on modeling of transportation systems. I continued research on this topic in engineering school faculty positions at Princeton University and University College London. I knew of the traffic studies and other research at GM R & D through meetings and their publications, and was interested to gain experience of applied research in industry. I joined GM R & D, where I have had the opportunity to work in a variety of research areas, including traffic safety, logistics, inventory control, and production system design, and to see results used in practice. It always impresses me how powerful even simple mathematical models can be in providing insight into system behavior.
Debra Elkins: I took a lot of classes in math, computer science, physics, and chemistry, and finally realized I liked sport computing and slick mathematics applied to real world industrial problems. I ended up in Operations Research, which lets me combine my interests in probability, super computing and high performance computing, simulation, and so forth. As a graduate student in the Industrial Engineering/Operations Research Program at Texas A&M University, I found out about working at GM R&D when I was at a technical conference. I decided to interview out of curiosity. I was really surprised and delighted with the people and the caliber of research going on within GM. My first major research project was to explore financial implications of agile machining systems for GM. While working on that project, I was poking around in risk analysis work, and connected with GM Corporate Risk Management, a group that wanted some help with probabilistic modeling of risks. Now I?m working on strategic supply chain risk analysis. I?m examining how to model the GM manufacturing enterprise, exploring the frequency and severity of business interruption events? anything that interrupts production operations?and considering strategic mitigation options that can reduce GM?s risk exposure. What excites me about my research is combining ideas from different subject areas, like math, computer science, statistics, and operations research, to develop novel modeling approaches and solutions for large-scale problems.
Jeff Alden: I basically pursued areas that I liked, excelled in, and seemed good for a future career. Since I really enjoy problem solving, math modeling, and helping people make better decisions, I naturally migrated to Operations Research. So I was sure what I wanted to do, but not sure where to work. Well, I attended a presentation about the research opportunities at GM R &D given by Larry Burns (now a VP at GM). It seemed like an ideal place to work, so I gave him my resume and soon accepted a research position at GM R&D. For the next decade, I researched production systems looking at throughput, maintenance, leveling, stability, agility, and cost-drivers. I?m now on a two-year rotation in GM Engineering managing development of decision-support tools and methods for engineering in a variety of areas that include test-scheduling, warranty cost drivers, and work load planning.