While digging through old scientific articles trying to ascertain when O.R gained a solid foothold in India, I stumbled on this gem from 48 years ago. The pdf version of this article that was published by "the defense documentation center for scientific and technical information, Cameron Station, Alexandria, Virginia" can be found here. The article is interesting for a variety of reasons. Among other things, it critically appraises the work of Russel Ackoff and Mahalanobis (about whom this non-blog will comment on in a later post) on using OR models for solving nation-planning problems in developing countries.
Words from the original document are in italics and any emphasis below in 'bold' is mine.
Ackoff asserted that a large role was both feasible and desirable. He predicted that extremely high returns would result from addressing national planning problems with operations research techniques in these countries. In striking contrast to this viewpoint, the ORSA president (Dr. Charles Hitch) at that time, stressed the risks of over-selling what OR has to offer the underdeveloped countries at the level of national planning, and apparently wanted OR'ers to focus on tactical and commercial applications at the project and industry level since 'OR is the art of suboptimizing' On the other hand, the document also notes that since then, Hitch has been a pioneer in adapting OR to national defense problems in the United States as Assistant Secretary of Defense (Comptroller). Hmm.
Other dissenters similarly commented on the characteristics of problems to which operations research can be most successfully applied, e.g., abundant and reliable data, a well-structured model, and a clear, reduceable objective function. [Dorfman] concluded that the conditions that are most propitious for the use of operations research tend to occur in "routine and technical problems" at lower and middling levels. The document includes examples that apparently point out the hazards of applying operations research techniques too quickly and broadly.
Salient features of this document include:
1. An open and frank conversational style of writing
2. The presence of constructive and sharp dissent without disparaging the worth or the author of that prior contribution
3. A strong emphasis on the practical method, which really distinguishes OR from other disciplines
- all three of which is mostly missing in the 'sterile' articles that we see published in recent times. When we arrive at the last paragraph that precedes the main body of work in this document (which consists of copious amounts of what we would almost certainly classify as 'analytics' today, e.g., causal statistical regression models, etc), we read this:
First, I am not particularly concerned with whether it might be more appropriate to apply the labels "econometrics," or "systems analysis," rather than "operations research," to one or both of these examples. Methodological purists may find it preferable to fit the examples into one or the other of these categories, but for my purpose, what we are concerned with is the application of quantitative analytical techniques to decision problems in the underdeveloped countries. From this standpoint, econometrics applied to practical, policy problems Is operations research.
At least for me, this argument amicably settles the non-debate on the dual noises emanating from our tribe on 'OR v analytics', but of course, it is wishful thinking that this practical discussion will fix the larger contemporary issue that is centered on 'brand labeling' and 'image perception' than anything that practically and directly affects our customer base, which should have been our #1 priority. An inclusive dual identity for a person is fast becoming the norm in this non-homogenous, 'globalized' planet, and to paraphrase Shakespeare, OR by any another name would add the same value to our customers.
The author of this informative 1963 document is Dr. Charles Wolf, Jr. A brief bio of this distinguished gentleman, and another one can be found here. By sheer coincidence, the May Informs blog challenge appears to be about 'OR and Analytics'.
Sunday, May 29, 2011
Friday, May 27, 2011
Memorable battle scenes on film - spot the O.R connection
This post consists of 'tragic battle' scenes from old classics. The aim is to find a popular O.R theme (however flimsy) in the clip, as we honor those who fought for a free world and laid down their lives so that we could continue to build O.R models, unconstrained. There are certainly many other war-movies with stronger military and civilian-OR themes, but these are five sentimental favorites. Enjoy the memorial day weekend as you think of other OR-themed movies!
5. Dirty Dozen (1967) - Jim Brown's incomplete TSP. What a ripper. A politically incorrect movie by today's "lofty" standards.
4. Von Ryan's Express (1965) Sinatra finds a feasible train route through a hostile network, but doesn't make it.
3. Haqeeqat (1964) - Final scene. The Indian army fails to build a robust supply-chain that is required for high-altitude warfare against the Maoists. Still remains the greatest Indian war movie ever made. An incredibly touching rendition of 'Kar Chale' by the great Mohammad Rafi that tears listeners up every time.
2. Enigma (2001) . Alan Turing, tragic genius, WW2 Bletchley park. OK, this is a relatively new movie, but the point is that critical 'analytics' battles have been fought by humble OR-types who saved countless lives and certainly did not nit-pick over whether it was 'OR' or 'analytics'.
1. Sholay (1975) Amitabh's fatal attempt to sever the critical link in the network and save lives succeeds. Favorite all-time movie scene in the most popular Indian movie ever made to date.
5. Dirty Dozen (1967) - Jim Brown's incomplete TSP. What a ripper. A politically incorrect movie by today's "lofty" standards.
4. Von Ryan's Express (1965) Sinatra finds a feasible train route through a hostile network, but doesn't make it.
3. Haqeeqat (1964) - Final scene. The Indian army fails to build a robust supply-chain that is required for high-altitude warfare against the Maoists. Still remains the greatest Indian war movie ever made. An incredibly touching rendition of 'Kar Chale' by the great Mohammad Rafi that tears listeners up every time.
2. Enigma (2001) . Alan Turing, tragic genius, WW2 Bletchley park. OK, this is a relatively new movie, but the point is that critical 'analytics' battles have been fought by humble OR-types who saved countless lives and certainly did not nit-pick over whether it was 'OR' or 'analytics'.
1. Sholay (1975) Amitabh's fatal attempt to sever the critical link in the network and save lives succeeds. Favorite all-time movie scene in the most popular Indian movie ever made to date.
Monday, May 16, 2011
Prescriptive Analytics: Optimize the history you are about to create
An important part of business analytics / OR practice is to assess the impact of a prediction-driven decision-support (PDS) system on:
a) the end-users aka consumers
Data-driven analytical prescriptions are based on perturbing a predictive model, which in turn is (usually) based on the observed collective consumer response to the same or similar products offered in the past. If the PDS recommends a clearly obvious pattern of decisions that differ from the past, it can change the behavior of even non-savvy customers, the cascading effects of which can be disruptive to the product provider's business. With all these mobile apps, the population of non-savvy customers is shrinking every day. Therefore, being proactive in designing the PDS to account for this feedback can be important.
b) the PDS
Some times, the decisions that the PDS recommends today (based on yesterday's history), become part of tomorrow's history, which in turn drives the predictor. However, we can be proactive in designing a PDS that is more likely to 'make' a friendlier history down the line. Furthermore, the 'inventory' of history you need to stock up on to calibrate your predictor can also be minimized. History, like gasoline, is often a scarce resource in OR practice.
a) the end-users aka consumers
Data-driven analytical prescriptions are based on perturbing a predictive model, which in turn is (usually) based on the observed collective consumer response to the same or similar products offered in the past. If the PDS recommends a clearly obvious pattern of decisions that differ from the past, it can change the behavior of even non-savvy customers, the cascading effects of which can be disruptive to the product provider's business. With all these mobile apps, the population of non-savvy customers is shrinking every day. Therefore, being proactive in designing the PDS to account for this feedback can be important.
b) the PDS
Some times, the decisions that the PDS recommends today (based on yesterday's history), become part of tomorrow's history, which in turn drives the predictor. However, we can be proactive in designing a PDS that is more likely to 'make' a friendlier history down the line. Furthermore, the 'inventory' of history you need to stock up on to calibrate your predictor can also be minimized. History, like gasoline, is often a scarce resource in OR practice.
Monday, May 9, 2011
Will the associates of #OBL move east?
Will the discovery of OBL in a posh hill-station in Pakistan increase the probability of finding the rest of his crew members? If so, will it be optimal for the other members to relocate from their current hideout to a safer place to minimize their chances of discovery but at the risk of briefly surfacing? What is the conditional probability that they are also in eastern Pakistan, given that OBL was found in that area? Does it increase or decrease? If Al-Q initially wanted to avoid an 'all eggs in one basket' situation, then they must have spread out and chosen to hide in places comfortably far away from each other. But on the other hand, if it was 'every rat is on his own', then they may have in fact have ended up, either independently or in collusion, gravitating toward the same geographical area.
It's my 2 cents worth of arguments based on just a flimsy data point that the latter case seems likely now. That they are hiding in places where they least expect the US to pop-in unannounced (Pakistan was never a concern, it now seems). A few hundred yards from a major military academy so far away from Afghanistan must have seemed pretty safe and for just for this reason alone, the raid achieved ultimate surprise. If this is the case, then there's probably a couple more in the vicinity. Pakistan-occupied Kashmir seems like another safe haven. It's further east, and most of the terrorist camps, whose recruits so predictably hit India after the winter snow melts to open up the passes, are located there. Furthermore, the element of surprise is gone for most part. Pakistan is unlikely to welcome further chopper incursions unless they are extremely well compensated.
So an Al-Q card-carrying member who lives west of Abottabad may feel the need to head further east. If he gets into India (which is just 60 miles away from Abbotabad!) through the porous border, there's 1.2 billion people to blend into.
It's my 2 cents worth of arguments based on just a flimsy data point that the latter case seems likely now. That they are hiding in places where they least expect the US to pop-in unannounced (Pakistan was never a concern, it now seems). A few hundred yards from a major military academy so far away from Afghanistan must have seemed pretty safe and for just for this reason alone, the raid achieved ultimate surprise. If this is the case, then there's probably a couple more in the vicinity. Pakistan-occupied Kashmir seems like another safe haven. It's further east, and most of the terrorist camps, whose recruits so predictably hit India after the winter snow melts to open up the passes, are located there. Furthermore, the element of surprise is gone for most part. Pakistan is unlikely to welcome further chopper incursions unless they are extremely well compensated.
So an Al-Q card-carrying member who lives west of Abottabad may feel the need to head further east. If he gets into India (which is just 60 miles away from Abbotabad!) through the porous border, there's 1.2 billion people to blend into.
Saturday, May 7, 2011
Informs Northeast Conference 2011 - summary
The INFORMS Northeast conference 2011 was held at U Mass, Amherst yesterday and today. There were many wonderful presentations from students and practitioners alike and it did not feel too crowded either. There was good representation from the OR-strong schools in the Northeast. In terms of industry participation, bigwigs IBM, Oracle (Retail), GE, the US Military, and a host of other interesting LLCs participated, giving students some valuable exposure to some real world business analytics and OR.
My personal favorites:
- The poster session: One example: Using OR to optimally do vehicle routing and sequencing to expedite power restoration after a major power loss in the network at multiple locations. Pretty innovative. and cool.
- Dr. Simchi Levi's plenary on the effectiveness of long chains in improving flexibility - Innovation in supply chain optimization continues...
- Optimal use of Airspace/runway capacity at congested airports - There were three talks featuring young OR/MS faculty members - I suspect we will hear a lot more about them in the coming years
- Agent based simulation by GE corporate research to optimally and practically manage a terribly complex 10-year project involving river dredging. There is something intuitively appealing about ABS and its utterly object-oriented approach to modeling and I do hope I get to use that idea somewhere.
Other comments:
- students (and some others as well) need to be doing more scientific-graphical presentations. More pictures - not the clip-art clutter / video junk type, but a well-thought out, informative visualization of scientific results that makes your approach more transparent to an audience that doesn't necessarily share your background. Mind numbing equation after equation is a kill-joy. Why tell when you can show?
- Of course, great work by the main chair, Dr. Hari J. of U Mass (that's thirty letters in a name, like his blogspot address). The 'health care and OR' sessions were quite packed (there were even some bonafide MD's presenting analytical stuff!) and hopefully this means that a lot more innovative work is on the way in this important area.
Nice work, and hope for an encore next year.
p.s: GPS sub-optimal response reconfirmed
This issue was mentioned on this non-blog a few months before, and now we have reconfirmation that for a brief time period, the GPS routing algorithm (Garmin, my favorite brand) does not always recalculate the optimal path if you deviate from the chosen route. The best route from Elmsford, NY to Amherst MA per google maps appears to be any one of three arc-disjoint pareto-optimal paths (practically). For a period of 10 minutes when I was off the GPS-recommended route in pursuit of an alternative optimal route (that was less congested historically), I was asked to get back to plan and every rejected exit increased my ETA. Finally, the GPS thingy gave up and recalculated from scratch and suddenly the ETA plunged to a value pretty close to the original value, as expected.
This strategy to 'get back to plan' is not uncommon and I don't consider this a defect (not yet). At large airlines, real-time aircraft routers and dispatchers (aka irregular ops) typically utilize such a scheme to minimize any unintended cascading disruptions introduced by wholesale re-optimization.
My personal favorites:
- The poster session: One example: Using OR to optimally do vehicle routing and sequencing to expedite power restoration after a major power loss in the network at multiple locations. Pretty innovative. and cool.
- Dr. Simchi Levi's plenary on the effectiveness of long chains in improving flexibility - Innovation in supply chain optimization continues...
- Optimal use of Airspace/runway capacity at congested airports - There were three talks featuring young OR/MS faculty members - I suspect we will hear a lot more about them in the coming years
- Agent based simulation by GE corporate research to optimally and practically manage a terribly complex 10-year project involving river dredging. There is something intuitively appealing about ABS and its utterly object-oriented approach to modeling and I do hope I get to use that idea somewhere.
Other comments:
- students (and some others as well) need to be doing more scientific-graphical presentations. More pictures - not the clip-art clutter / video junk type, but a well-thought out, informative visualization of scientific results that makes your approach more transparent to an audience that doesn't necessarily share your background. Mind numbing equation after equation is a kill-joy. Why tell when you can show?
- Of course, great work by the main chair, Dr. Hari J. of U Mass (that's thirty letters in a name, like his blogspot address). The 'health care and OR' sessions were quite packed (there were even some bonafide MD's presenting analytical stuff!) and hopefully this means that a lot more innovative work is on the way in this important area.
Nice work, and hope for an encore next year.
p.s: GPS sub-optimal response reconfirmed
This issue was mentioned on this non-blog a few months before, and now we have reconfirmation that for a brief time period, the GPS routing algorithm (Garmin, my favorite brand) does not always recalculate the optimal path if you deviate from the chosen route. The best route from Elmsford, NY to Amherst MA per google maps appears to be any one of three arc-disjoint pareto-optimal paths (practically). For a period of 10 minutes when I was off the GPS-recommended route in pursuit of an alternative optimal route (that was less congested historically), I was asked to get back to plan and every rejected exit increased my ETA. Finally, the GPS thingy gave up and recalculated from scratch and suddenly the ETA plunged to a value pretty close to the original value, as expected.
This strategy to 'get back to plan' is not uncommon and I don't consider this a defect (not yet). At large airlines, real-time aircraft routers and dispatchers (aka irregular ops) typically utilize such a scheme to minimize any unintended cascading disruptions introduced by wholesale re-optimization.
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