Wednesday, 27 August 2008

Operational Research and Design

One of the subject headings in the International Abstracts in O.R. (IAOR) is "Design". Over the years, there have been comparatively few abstracts which were classified under this heading. I wondered why. What sort of papers would be classified as "O.R. in Design"? One tends to think of design in connection with small (comparatively) items or matters, when one is not concerned with aesthetics. Things like household equipment, the layout of roads, small engineering items. A useful text is The Design of Everyday Things by Donald A Norman -- which doesn't mention O.R. but does discuss optimality quite frequently. But this aspect of design does not lead to academic papers. Manufacturers employ designers to make money, not to produce learned papers. Look at the jets in the rotor of a dishwasher; someone has designed them, found the best angles, positions and sizes, in order to efficiently and cheaply carry out a dishwashing cycle. Hard work -- hard O.R. work -- but not worth writing about. Sometimes the results of design are commercial secrets. When I was recently out of my postgraduate training, I went on a site visit and asked about a piece of equipment on the production line. Had the company patented it? No, because a patent would be visible to their rivals.

But sometimes one wishes that the results of design as the result of a modelling process could be made public. By doing that the benefits of one person's analysis could be usefully shared. I come across such an example regularly. What is the optimal separation between cycle racks? By the swimming pool, there are six racks, at 45cm apart. The outermost racks are therefore 225cm apart, and one can park seven bicycles in the space. Near the office, there are four racks, 100cm apart. Two bikes can be parked in each gap, so in 300cm there are eight bikes. Which is better?

Tuesday, 26 August 2008

Operational Research and Waste Management

In the International Abstracts in Operations Research (IAOR), every abstract is given at least one subject category. We have a list of about 200 such, and an important part of the added value of IAOR is the fact that this assignment of categories takes place -- by an expert in O.R.. In addition, many papers have a free format description added, which is indexed in the print version and becomes a part of the online record. Over the last few years, there have been an increasing number of papers which have had the free format "Waste management" added. These papers have dealt with vehicle routing, crew scheduling, location of obnoxious facilities and other topics. It seems that this is a growing area of application for O.R..

I have my own problem in waste management, and have considered it from an O.R. perspective. How should I deal with the clippings from the hedge at home? The hedge is about 50 metres long, nearly two metres tall, and is privet. I use electric trimmers, once or twice a year. Privet branches tend to be long and straight, but there are a lot of them. The options are (1) to load them into the car and take them to the council dump, (2) to buy sacks from the council to be taken away by the garden refuse collection, (3) to burn them on a bonfire, (4) to shred them, (5) to leave them in a heap to rot slowly.

(1) and (2) are expensive options, and I would derive no benefit; (3) I reject on the basis that I do not like polluting the air and have no space for a fire; (5) is unsightly in the garden. So I shred the cuttings. But how? Over the years I have found that I can get a lot of shredding done with the rotary mower, simply by driving the mower over the trimmings as they have fallen on the ground. The method fails if the long straight branches have been raked -- the random alignment of branches is important. Some branches are not shredded by this process, and those go though a electric shredder -- which I do not use for the whole process as it is slower than the mower. Then I have to compost or use the shredded wood and leaves as mulch -- so I benefit from the nutrients; the garden is not totally organic, but I feel that I have done a little for the planet, and found my personal optimal solution. Now how can this process be written up as a journal paper?

Wednesday, 20 August 2008

O.R. and the Infrastructure (3)

Another thought about the hidden science. In the U.K. (and I guess in many other countries) most traffic lights (whatever you call them) at road junctions are controlled by computer. Detectors are located close to the stop line and also in advance of that line, indicating the presence of vehicles waiting and approaching. (Next time you are cycling or walking past traffic lights, have a look for black tar-covered lines in the tarmacadam, which cover detector wires, or look for miniature radar sets on the lights themselves.) The logic behind the programs that control the lights is developed by O.R. scientists. In the programme about infrastructure "Britain from Above", the presenter visited a traffic control room, where the staff had the power to change lights when their traffic monitoring equipment (including TV cameras) detected congestion. It was left unsaid that most of the time the traffic flow is controlled automatically; the people in the control room had to deal with the exceptions, the unusual. Why can't the computer control be extended to cover these exceptions? Cost and complexity. It would cost too much to build in rules for exceptional cases, which would be complex. It is good O.R. (IMHO) to know when to stop building too complex a model. Besides, traffic control has multiple objectives, and the importance of the different objectives changes with the time of the day and much else.

O.R. and the Infrastructure (2)

I'm sure that I shall return to the expression that "O.R. is the hidden science" many times. In the T.V. presentation of "Britain from Above" already mentioned, the presenter observed part of the distribution chain that supplies shops and (especially) supermarkets. In a throwaway remark, he mentioned the 15-minute time windows for collections and deliveries at many stores. And these are part of the world of the O.R. scientist. There have been numerous papers on vehicle routing, and many software companies employ O.R. staff to provide tools for scheduling vehicles with time windows. It is a testimony to the success of O.R. that these hidden tools work, and so everyone can take them for granted! Yes, even the best systems can go wrong, but when was the last time that you couldn't buy an everyday item of food in your local supermarket?

Wednesday, 13 August 2008

O.R. and the infrastructure

90 lengths today! (see yesterday's blog)

This week I watched the first episode in a new BBC TV series, Britain from Above. The opening programme focused on the infrastructure which lies behind life during a typical day in Britain. So there were mentions of transport, electricity supply, water supply and treatment, communications and so on. The filming was of a very high quality, and there were some good computer graphics, although quite often there was too little time to appreciate the message. The programme tended to move from topic to topic, trying to hold the viewer's attention -- and assumed a limited attention span.

I very much enjoyed reading Infrastructure: The Book of Everything for the Industrial Landscape which looks at the engineering behind a nation's infrastructure, and the BBC programme touched on this. But it also looked at aspects of control, and I wondered what would have happened if the presenter had been familiar with the work of O.R. scientists. For those who know how ubiquitous O.R. is, the programme emphasised that O.R. is the hidden science behind many things.

Sadly, for commercial reasons, much of the practical work of O.R. professionals in practice is never published. Why should you tell the world what you have done, and how you have done it, when your results could be exploited by your competitor?

To take one example from the programme, one that caught the attention of several commentators. At the end of the programme "Eastenders", there is a great surge in demand for electricity as well over a million kettles are switched on across Britain. The electricity industry has to cater for this demand, and we saw the man with the responsibility watching the demand rise, and bringing hydroelectric power stations "online" to cope with the demand. More power was bought from France. The same electricity industry uses O.R. to deal with the varying demand, with models (some of which are as simple as large linear programs) that show when diferent means of generating power should be used. When I talked about this with a researher in the industry, he spoke about the sudden demands for power during and at the end of TV programmes, and also of the difficulties that are created by having a cheap night-time tariff for electricity. Many users have timers which switch on appliances at the start of this tariff.

Tuesday, 12 August 2008

Measurements in operational research

Today I swam for the hundredth time this year in the city swimming pool here in Exeter. It is a 25 metre pool, and -- according to my spreadsheet -- I have swum 8300 lengths this year. (I deliberately swam enough lengths today to make the total a round number, and the mean an integer.)
But, how far have I actually swum in that pool this year? I keep a spreadsheet for these swims, and that is updated every time I swim, so the number of swims in the city pool is reliable. I have swum once elsewhere, and we are discounting that five minute splash in a cold, open air pool. There are three obvious sources of error.
First, I may have miscounted. There is no mechanism for recording the lengths except my head, and I know that sometimes I lose track. But to counter this source of error, I usually swim with my wife, and she also counts lengths and we can generally verify the number of lengths each has swum (she is a little faster); I also know how fast I swim, so the clock on the wall of the pool gives a safeguard against gross error. As I swim an even number of lengths, my count is likely to be in error by \plusminus 2 if at all. I would hazard that I have made an error on at most 5 occasions. So the count of the lengths is 8300 \plusminus 10
Second, I do not always stay in the same lane of the pool, so I don't swim exactly the length of the pool. But simple geometry tells me that even if I swim slightly off straight, the difference between what I swim and the length of the pool is very small. We are talking about a variation of \plus 0.05% at most, say 4 lengths.
Third, I trust the pool builders to have measured correctly. But here is the most intriguing source of error. The pool is not exactly 25 metres. There is a tolerance because it was surveyed with measuring line when it was built. Everyone believes that it is exactly 25 metres, but the tolerance is probably \plusminus 150cm (6 inches) -- about 0.5%
So, all in all, I have not swum exactly 207.50 kilometres this year. The extreme range is
8294 * 0.024850 to 8314 * 0.025150 kilometres, i.e. (206.1 to 209.1) But that is the extreme range, and the confidence interval is smaller -- an exercise for the reader.
Why does this matter?
One, the Olympic Games are currently happening. How accurately are lengths of tracks and pools measured? The times of races are recorded very accurately, because we are very good at recording time. But how much tolerance is there in the distances?
Secondly, for O.R. professionals, how often do we believe in spurious accuracy of data? When I learnt about L.P. in the oil industry, we were told a cautionary tale, of the analysts who checked their data; one measurement of viscosity of crude oil was always given as an integer, a small integer. This was then processed through the L.P. model. Where did this value come from, they asked. As one should, they checked. The data was supplied by an experienced worker, who dipped his thumb and forefinger into the crude oil, rubbed them together, and pronounced the measurement. Now, far too often, I see papers submitted for journals where there are tables of results quoted to six or more significant figures. Where did these come from? Usually from the analysis of a few dozen observations that were each measured to two or three significant figures. The best models in the world cannot conjure more accuracy from the model than was in the source data; but all too often we forget that, at our peril.
The results are only as good as the data.