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OR/MS Today - December 2001 Q&A ![]() Cruising along at 75, operations research pioneer Saul I. Gass has done just about everything in his remarkable 50-year career ... except slow down By Peter R. Horner When noting the lifetime work of operations research pioneer Saul I. Gass, it probably makes more sense to name the few things he hasn't done rather than attempt to compile a comprehensive list of all of his achievements and accolades. Gass didn't, for example, invent linear programming. He just learned it from those who did, people like George Dantzig, and then Gass went out and wrote the first textbook on the subject. His text, "Linear Programming" now in its fifth edition, has introduced LP and OR to literally thousands of students since it was first published in 1958. After 25 years on the practice side highlighted by stints as manager of the Project Mercury Man-in-Space Program and manager of IBM's Federal Civil Programs, and 25 more years as a highly decorated professor at the University of Maryland, one could say that Gass "wrote the book" on operations research and the management sciences. He didn't. He just co-edited (along with the late Carl Harris) the "Encyclopedia of Operations Research and Management Sciences." Saul's career in operations research dates back to 1952 the same year the Operations Research Society of America was founded when he went to work for the Directorate of Management Analysis in Washington, D.C., at a time when OR, LP and computers were in their infancy. Legend has it that Gass crunched numbers on the first Univac computer ever produced. Not true. The first Univac machine went to the U.S. Census Bureau. Gass had to wait for the second Univac computer ever produced, the one that was installed in the basement of the Pentagon while he was working for the Air Force upstairs. Gass served as president of the ORSA and Omega Rho (the international operations research honor society) and as vice president for international activities of INFORMS. He's a recipient of the Kimball Medal for service to the society and the profession, the INFORMS Expository Writing Award and the Military Operations Research Society's Jacinto Steinhardt Memorial Award for outstanding contributions to military operations research. Gass was named a Fulbright Research Scholar, a University of Maryland Distinguished Scholar-Teacher and the Dean's Lifetime Achievement Professor at the Robert H. Smith School of Business at the University of Maryland. We could go on and on, but, like we said, it would be easier to list the few things Saul hasn't won, like the Super Bowl. (He did, however, create and host the Knowledge Bowl at INFORMS meetings.) Gass, 75, retired from the University of Maryland earlier this year, but anyone who knows Saul knows he is not the retiring type. Gass, who used to organize and compete in 10-K runs at INFORMS conferences, just keeps going and going and going, like an Energizer Bunny minus the drum, pink suit and floppy ears. He continues to serve INFORMS in a variety of capacities; he's working on the sixth edition of his text, "Linear Programming"; he's still actively involved in his multiple research interests (LP, large-scale systems, model validation and evaluation, game theory, multi-objective decision analysis and the application of operations research methodologies); and he's looking forward to traveling around the world a few more times with his wife, Trudy. Saul Gass hasn't really done it all when it comes to his career or his life; it just seems that way. In mid-October, shortly before he was saluted by colleagues and former students at special sessions organized in his honor at the INFORMS meeting in Miami, Saul sat down long enough to be interviewed by OR/MS Today Editor Peter Horner. Needless to say, when the subject is operations research, Saul Gass has plenty on his mind, and he doesn't mind speaking it. OR/MS Today: Let's start at the beginning. How did you become involved in operations research? Saul Gass: It's a long story. You sure you want to hear it? OR/MS: Give me the Reader's Digest version. SG: I earned my master's in mathematics way back when there weren't any jobs. I applied to various places and sent out 100 letters. The only bite I got was a civil service job in the Los Angeles area. This was in 1949. My wife's family had moved to California from Boston, so I said why not? My B.S. was in education and I thought I was going to teach high school math, but a semester of student teaching in the best high school in Boston convinced me that that wasn't for me. So I accepted the civil service job. I thought I was going to work at an Air Force bombing range out in the Mojave Desert. It turns out there was a group in Los Angeles called the Aberdeen Bombing Mission doing ballistic work for the Air Force. So I worked in L.A. I wasn't too happy about L.A. or bomb ballistic work, so a few years later I applied for another civil service job in Washington, D.C. They asked me to come out for an interview. I asked if they were going to pay for my trip. They said no. I figured that was the end of it. A few weeks later I got a notice to report for duty. That took me by surprise, but I looked into it and the job offer was legitimate. Trudy and I and our six-month-old son drove east in my first car, and I joined an Air Force group called the Directorate of Management Analysis at the Pentagon. I had no idea what it was. George Dantzig was the group's chief mathematician. The second day I was there, George gave me some of his papers on linear programming. That's how I got involved in operations research. OR/MS: Had you ever heard of operations research or linear programming before you met Dantzig? SG: No. But you have to remember this was 1952. ORSA didn't exist until that year. There really wasn't much published on linear programming. No one was teaching LP in schools. I learned LP at the feet of the people who developed it George Dantzig, Alex Orden, Walter Jacobs, Julian Holley and others who were at the Pentagon at the time. OR/MS: What kind of work were you doing? SG: I was assigned to the mathematical formulation branch. We set up U.S. Air Force problems logistics and deployment problems to be run on IBM accounting equipment geared up to do computational work. We also had access to the first computer (SEAC) at the National Bureau of Standards. The Air Force and Dantzig's group had sponsored the purchase of the second Univac computer. The first one went to the U.S. Census Bureau. The second one went into the basement of the Pentagon. When the first codes were written not by me, because I wasn't a coder we would set up problems, check the code, make sure things were going right. Then we would do some production runs, do some analysis and do some research. That's' how I got into the area of parametric programming. I published my first paper in Operations Research in 1953 with Tom Saaty. I think you'll find many people with my background who got into OR the same way I did by happenstance. They were mathematicians and they just sort of said, "Hey this operations research is some interesting stuff." OR/MS: You became involved not only with operations research, but with the professional society, ORSA, the forerunner of INFORMS. SG: Yes. I joined ORSA in 1952, shortly after it was founded. I went to a conference at MIT and heard [George] Kimball and others talk about some of the work they were doing. I found out that there were OR summer courses at places like MIT. I took an operations research course from Joe McCloskey at American University, a course on linear programming from Alan Hoffman, and I learned game theory from Al Tucker and Harold Kuhn. It started to sink in that operations research was the type of mathematics that I enjoyed and that I could do well in. OR/MS: What did OR do with the math that you found so compelling? SG: Operations research basically said, "Here are some real-world problems." They weren't engineering-type problems like how to build a bridge or how to design a jet engine, problems I wasn't good at. OR was about decision problems. How do you choose among alternatives? It just seemed to be an intriguing look at applied mathematics. And there was some nice theory behind it that I could appreciate and understand. That was important. OR/MS: Decision-making is such a fundamental human activity ... SG: That's true, but it took me and I think maybe even the profession a while to figure out that that's what operations research is all about. People ask me what I do. I'll mention operations research, and then I'll go ahead and say that we look at the art, the science and the practice of decision-making. What we do is bring a basic framework to decision-making in terms of how you evaluate complex decision problems. OR/MS: For years people have struggled to define operations research. You wrote the "Encyclopedia of Operations Research." Give us, once and for all, the definitive definition of operations research. SG: In the first edition, we tried not to define it. We said for those readers who are interested, here's how other people have defined it, and then we quoted various sources including the definition that ORSA was using. ORSA more or less defined it in terms of determining the efficient use and allocation of limited resources. Today, I say that OR is a scientific approach to decision-making. You're applying mathematical and other techniques to decision problems in all areas business, industry, government and the military. OR/MS: Ironically, the vast majority of business and industry leaders have never shown any knowledge of, much less appreciation for, operations research. SG: Let me put it this way: I think those groups that have used the techniques of operations research appreciate it. Go to the petroleum industry, for example. It's all run using LP and related ideas. Take a look at airlines from the point of view of their scheduling. It's all done with OR techniques. They can't help but appreciate the fact that we have some analytical techniques to really help them be more effective and more efficient. Whether or not they realize where it comes from and the history behind it that it's really operations research that's another matter. It's the age-old identification problem. I'm on the INFORMS Public Information Committee and the big question we face is, "How do we brand our products and services?" The phrase the committee uses is, "OR Inside." To me, OR is the hidden ingredient in many things. OR/MS: Does it frustrate you that after 50 years OR still doesn't have anything close to universal brand recognition? SG: I see it a couple of ways. On the one hand, I'm not frustrated because I see the techniques being used and being used well. That's a big plus. On the other hand, when my profession, OR, doesn't get the credit, that's bothersome. You've got to remember I worked out of Washington my entire adult life, and I'm more tied into governmental activities than industry activities. I've seen it in the Washington area many times. When the energy crunch hit us in the 70s, the government rounded up some great people to address the problem. They set up an intricate and novel energy modeling system that was basically linear programming, but there was never any mention of operations research. OR/MS: It's the same story today, only this time it's "supply chain management." SG: Everyone talks about supply chain management, which is basically operations research. Certainly, supply chain management would not be possible without all of the techniques and ideas that OR folks have developed over the last 50 years. We can put it together now because we have powerful computers to collect the data. We know how to manipulate it and analyze it, but you don't see it referred to as operations research. Case in point: I was thumbing through the Oct. 3 issue of Fortune magazine in the doctor's office and there was a spread on supply chain management. The article mentioned one of our OR guys, the editor of one of our journals, the head of a supply chain management center. The article had vestiges of operations research all over the place, but you never saw the actual phrase "operations research" used. That's what we're fighting. OR/MS: Sounds like the name branding is a tougher dilemma than the Traveling Salesman Problem. SG: Funny you should say that. Let me tell you a Traveling Salesman Problem story. A number of years ago, there was an article in Math Monthly, the membership magazine of the American Mathematical Association. I'm reading this article on combinatorics and they mention the Traveling Salesman Problem. The author explained that computer scientists like to use interesting names like Traveling Salesman to describe their famous problems. I wrote a letter to the editor saying the Traveling Salesman Problem did not come out of computer science, it came out of operations research. I gave a history of the name and the Knapsack Problem from Dantzig's original paper. The letter had to go through a refereeing process, but they finally published it. That incident sums up our problem: People from other fields are usurping our ideas and we're not getting credit for them. OR/MS: You've mentioned George Dantzig several times. What was your first impression of him and how has he influenced your career? SG: George has influenced me in many ways over many years. George is a very kind gentleman, but he can be very direct. If he doesn't like something, he'll let you know. I first met him at the Pentagon 50 years ago, and he was very kind to me in terms of giving me his papers and helping me with research problems. He left for Rand six months after I arrived, but I stayed in contact with him, read his papers and saw him at conferences. He was always very encouraging. Years later, when I was with IBM and had a chance to go back to school and get my Ph.D. on an IBM fellowship, I wanted to go U.C. Berkeley because George was there. George thought it was a grand idea, and it worked out very well. George was my dissertation advisor, and the only person who asked a question at my oral. OR/MS: So what was Dantzig's question? SG: At Berkeley, you had to be ready for anything. They gave me a paper outside of my field to discuss. It had to do with queuing theory. I didn't understand much about that stuff, but I knew from working at IBM how to make presentations. During the course of my discussion, I used the word "convolution." George asked me for the definition of convolution. Fortunately I was ready for that one. OR/MS: When you organized the Dantzigfest a few years back, it was obvious that you have a great deal of admiration and respect for Dantzig. SG: In terms of the people who were really responsible for the development of the field of OR the theoretical aspects and the continuing research methodologies George is right at the top of the list. I think he got short-changed on the Nobel Prize in 1975. That year T.C. Koopmans and L.V. Kantorovich received it for their work in the "Theory of Optimum Allocation of Resources." Since that time a number of people have won the Nobel Prize based on work that can be traced to George. When I got to the University of Maryland, I nominated George for an honorary degree. You know, George earned his bachelor's degree in mathematics from Maryland. OR/MS: It seems you two have crossed paths many times. SG: Fortunately for me, that's true. OR/MS: When you look back on your career, certainly your work on the Project Mercury's Man-In-Space Program in the early 1960s must have been a highlight. SG: It was, indeed, an interesting time. I left the Pentagon after 3 1/2 years because my research group was being dissipated. There was the McCarthy scare in Washington, and we had some people on our staff who thought they would get bounced, so they left. The Eisenhower administration closed down a lot of research efforts. The timing was right to look around for something else. IBM was advertising for what they called Applied Science Representatives. These were technical people they needed to help salesmen sell computers. So I joined the local IBM sales office not in a research capacity and went through their sales school. I had a grand time working with the salesmen. I learned a lot working in that environment. I eventually left to go work for a consulting company, the first consultancy group in the country to get into operations research. Then the space program opened up and IBM won the contract to do the orbital calculations for Project Mercury. A friend of mine from IBM was put in charge of the project and he asked me to come back and work with him. Project Mercury fascinated me. I headed up the simulation aspect of the worldwide tracking system. Then, a couple of years later, I was named project manager for IBM's Mercury effort, and this was five days before [Alan] Shepard's flight. OR/MS: Talk about critical decision-making. I can't think of a more exciting job for an operations research practitioner. SG: It was a most challenging time. We had duplex computers at the Goddard Space Center in Greenbelt, Maryland. I used to go down to the Cape before all the manned space flights. It really was exciting and a top achievement in my professional career. I learned a helluva lot that carried over to what we do now in operations research such as how to validate systems. I learned a lot from NASA and IBM engineers about how to pull a really complex system together. By the way, that was the first instance of real-time computer decision-making with a man in the loop. We had to determine whether or not the orbit was a go or no-go. We had to analyze data coming in in real time from the Cape and tracking sites all around the world. We'd update the orbit, determine retrofire and things of that sort. OR/MS: How did it work? SG: The computers that determined an orbit go or no-go were the two IBM computers at the Goddard Space Flight Center in Maryland. Data came up from the Cape over high-speed lines. We had to take initial radar and telemetry data right after launch to determine whether the orbit was going to be a proper one so they didn't have to abort it. We would send information back in terms of whether it was a go or no-go. There was a red light and a green light. We'd also flash the number of possible orbits. The number always turned out to be seven. The reason it always turned out to be seven was because we only had three computer bits available to us to send the information down, and the most we could get out of that was the number seven. The number of orbits was always, much more than that. OR/MS: So who determined if it was go or no-go? SG: The computer did. We'd look at the computer output. We had a plot, a nominal plot. If the plot was deviating from normal or something didn't seem right as far as the computer system was concerned, we would throw a switch to go from one computer to another. I did that on Shepard's flight I can't recall exactly why and it worked. The other machine picked it right up. It was a sub-orbital flight out over the Atlantic. I can't recall any problems we had with the computers. When IBM first started with Project Mercury, IBM wasn't going to be involved with the go/no-go decision, but NASA knew they had to get a better system so IBM picked up that task as well. They always had range safety down at the Cape. If things didn't look right if it looked like the rocket would hit Miami they would just blow it up. That was the back-up system. OR/MS: Where was the OR in all of this? SG: The OR was in the simulation of the worldwide tracking system. But I can't say that I looked at it as OR at the time. Our particular problem was, How are we going to handle the simulation? Should it be a next event or fixed-time interval simulation? The system itself was a very complicated programming system. The OR was in the modeling of the system and the testing of it. We had to get the system accepted by NASA. I remember a meeting with NASA where we said here are the simulations we're going to run. It was very important in terms of having abort situations, because we were training flight controllers at the same time. We actually sent data out to sites and they sent information back to us. We would simulate lift-off and a three-orbit pass. We'd put anomalies in to make sure the program could pick these things up. IBM managed to get a great group of programmers together who were really breaking new ground, especially in terms of real-time data processing. OR/MS: After all these years, do you consider yourself a mathematician or an operations researcher? SG: If I look at my first two degrees, I'm a mathematician. From the point of view of my overall profession, that's operations research. However, in terms of what job I've held the longest, that would be college professor. OR/MS: You didn't join the ranks of academia full-time until 1975. By that time, you had compiled a distinguished 25-year career on the practice side. Why the change? Did you always want to be a college professor? SG: Not really. I got into the teaching mode in Washington. I thought I might get into teaching at some point in my career, but I never thought I would become a university professor. It never crossed my mind. In the early 1950s, Dantzig taught the first linear programming course at the U.S. Department of Agriculture Graduate School in Washington. When Dantzig left, it was picked up by an Air Force consultant George O'Brien, who was a mathematician at one of the local universities. A year later, O'Brien left and he asked me to teach it. After that, I taught LP for many years, usually on Monday nights at the Agriculture Grad School, at American University or at George Washington. Even when I got my Ph.D. in 1965 I didn't think about a teaching career until I got out of the consulting mode in the 1970s. When an opportunity at the University of Maryland opened up, I took it. I didn't even have to move. OR/MS: As much success as you had in business and consulting, you might have exceeded it in academia. SG: I hope that's the case. I've certainly enjoyed teaching, but things have changed over time, especially in the business school. The students have changed, the courses have changed. But that's another story for another day. OR/MS: Why wait? Let's talk about it now. In your opinion, what's right and what's wrong with OR grad school education today? SG: It depends on where OR is being taught. First, let's look at MBA programs. When I joined the business school at Maryland and I think it was true then for most MBA programs there was a solid base of at least one semester of both statistics and operations research or management science that were required. My school called it management science because it sounded better coming out of B-school, whereas industrial engineering departments generally called it operations research. Over the years, because of complaints by MBAs who didn't have strong mathematical backgrounds, the OR courses have sort of disappeared in terms of core courses. That's what happened in my school. Now they get a semester of probability and statistics, and that's it. They don't get anything about linear programming; they don't know anything about AHP, network models or simulation. I think that's a shame because these MBAs won't be conversant with what's going on in their own organizations. OR/MS: Do MBAs need to be analysts? SG: From my standpoint, I was never trying to train MBAs to be analysts. They're not going to be OR analysts. I wanted to give them a strong appreciation of operations research, so people who work for them who might be OR analysts can come to them and say this is what I've got, here's my computer printout, here's my PowerPoint presentation, and they would better understand what's going on. That's the thing I was driving at. OR/MS: What happened? Another public relations battle lost by operations research? SG: I think the operations research and the management science people just didn't have a strong voice within the overall business school world, especially among the accreditation agencies and committees. They dropped the requirement, for example, of operations management where they would usually do OR. Marketing, Finance and Accounting, on the other hand, had a very strong voice in setting up the program. I've seen it in my school. We formed a committee five years ago to look at what was going on, and none of the OR people were on the committee. So we got chopped out. OR/MS: OR seems to be faring better on the industrial engineering side of the equation. SG: I can't speak to that, but yes, I imagine it is. There are plenty of jobs for someone with an OR degree from a good industrial engineering school, someone with good computer experience. If you really want to train people for jobs, that's a great field. There's some promising undergraduate activity even in business schools. There's a big push for information systems people, and many schools have recognized that they should have some modeling experience. Give them an operations research course that could be required or at least an elective. We don't normally look at the undergraduate area as pushing out OR people, but I don't see why it can't. Let's give these students some OR training a background modeling course, some computer work so they can go ahead and get good jobs. On the Ph.D. level, I think we're OK. We're still running our Ph.D. programs in OR at Maryland and I think most schools are doing the same. The question is, where will they be placed: in industry or academia? There's also a blip on the horizon that indicates that math programming is picking up along with applied mathematics. Many schools have an optimization group. It's usually buried in computer science, but they're doing OR. To answer your question, the OR education picture is a bit muddled. If you just look at the business schools, there's a tendency to think we're going down the tubes because so many business schools have dropped the MBA OR component. I think that will cycle back four or five years from now when they find out that MBAs can't do much analysis at all and they don't know anything about these things. OR/MS: Given the muddled education picture, are you still optimistic about the future of the OR profession in general? SG: I'm optimistic in terms of OR's future, but there are certain things that are always with us and they seem to be bearing down on us a little stronger these days. If you want to be on the pessimistic side, we still have these professional identification problems. I'm also concerned about the professional quality of our work and our ability to train people to do quality projects. Outreach to other disciplines, education of the next generation these are the things I'm worried about. Then there's this aspect that other professions are usurping OR methods and we're not getting credit for it. All of these things have been with us for a long, long time, but we still seem to be doing well. If you look at the track record of what OR has done over the last 50 years, we've solved all the easy problems. They're done. Who did them? Either OR people or certainly OR techniques. All those operational problems we've been talking about airline scheduling, shipping, petrol-chemical problems, supply chain management, things of this sort we're there. The challenge now is to move into new areas and solve new types of problems. I'm confident the OR profession can do it. Whether or not we will do it and whether or not we get credit for it that's another question. Even if we don't get credit, at least we should be able to say we were there. OR/MS Today copyright © 2001 by the Institute for Operations Research and the Management Sciences. All rights reserved. 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