Announcing simulation model "Conference optiloo"

Conference optiloo will be a visual simulation model designed for large conference centres where the management wish to reduce congestion at their toilets at the end of addresses and speeches.  It should be based on the premise that most conference centres have used national or international guidelines for the number of washrooms on the assumption of a 50:50 split of genders among the delegates.  These guidelines should be adequate for a wide range of splits of genders from roughly 20:80 to 80:20.  Conference optiloo will be designed to assist the planning where the gender split is more heavily weighted than these figures suggest.  Examples might be conventions for women in management or organisations where males are most numerous.

The simulation model will use observed data from conferences to measure the demand for washrooms after long plenary sessions, giving typical time-dependent rates of arrival for users during the breaks between such session.  Using publicly available data for the gender-specific distribution of occupancy time of washrooms, adjusted if empirical evidence supports the hypothesis that these times are reduced when the user is aware of a queue outside, the model will provide the conference management staff with visual information about the build-up of queues at restrooms.  The model will offer such staff the ability to change the gender allocation of each washroom area from male, to unisex, to female, again making allowance for empirical behaviour of patrons in a unisex facility. A fast-running model in the background will complement the visual output with statistics from several independent runs of the model, which can be used to make informed comparisons of alternative systems.  Its use could be extended to large theatres, sports grounds and auditoria

This simulation model is bound to have widespread application as seen in this blog entry.  Please note that the model does not actually exist, nor that I am not planning to research or write it - but the idea is offered to anyone who wishes to develop it further - but please credit me with the idea!

Silicon Valley Men's Room Problem

Sooner or later, most lecture courses on queues mention the problem of queues for toilets.  Generally the focus is on the provision of facilities in public buildings, and the difference between the genders.  One writer summed up the problem that exists in theatres and similar places where the demand for toilets peaks during a short period of time; if there is a queue for the men's room, as well as for the ladies' room, then there is a real design problem.

The UK national newspaper, The Independent, published a picture and article yesterday with a twist to this story.  It showed Dan Ackerman's picture (above) of a queue for the men's room, and no (visible) queue for the women's.  It was taken at the Worldwide Developers Conference (WDC) in San Francisco.  What does it say?  The majority of delegates at the conference were male, but the provision in the conference centre assumed a moire even mix of delegates.

The picture started a Twitter account whose aim is to see enough women in software development that there would be a queue at the women's restroom.

But OR is not just about modelling queues; it should aim to reduce congestion.  What might be done in the conference centre for such an event as the WDC, where the organisers know that there will be an imbalance?  The same problem applies in reverse for conferences targeting women.  If there really only two restrooms, then there is little possible unless all the provision is made private (i.e. no public urinals).  But at a large conference, then one could designate some restrooms of one gender to be temporarily for the other.  Yes, the minority might have to walk, but the majority would not have to cross their legs in the queue outside the doors. 

Step forward someone who attended the WDC and can give figures for the number of accessible restrooms for each gender, and step forward someone who could model the system.

Silly statistics, family style, Kipling and Bondi

The average UK mother of children aged 2 to 10 is asked 288 questions per day.  An online newspaper article (with comments) is here.

This was the result of a survey of 1000 mothers.  Just imagine how they did it!  How many days' observation? 

Many years ago, the late Sir Hermann Bondi, who had strong links with OR in the UK, told an audience the following.

Little children, up to the age of eight, nine, or ten, are constantly asking the question "Why?".  One aim of education is to stop them asking that question.  Education has its failures.  The resulting failures are called scientists.

One of the comments quoted Rudyard Kipling's poem, "I KEEP six honest serving-men", from the "Just So Stories", which I have heard quoted as being apposite for an Operational Research Scientist.

I KEEP six honest serving-men
(They taught me all I knew);
Their names are What and Why and When
And How and Where and Who.
I send them over land and sea,
I send them east and west;
But after they have worked for me,
I give them all a rest.

I let them rest from nine till five,
For I am busy then,
As well as breakfast, lunch, and tea,
For they are hungry men.
But different folk have different views;
I know a person small—
She keeps ten million serving-men,
Who get no rest at all!

She sends'em abroad on her own affairs,
From the second she opens her eyes—
One million Hows, two million Wheres,
And seven million Whys!

A royal location problem

Last week I came across an interesting location problem.  Location problems are all about deciding where to site one or more facilities or buildings to meet some specific criteria.  There are several mathematical models which are used to help with these problems, and countless books and articles have been written about them.  My PhD student, now Professor, Shams-ur Rahman, modelled the location of health facilities in Bangladesh; one of the constraints was political - each sub-district had to have the same number of health centres, even though this meant that the locations were sub-optimal on other criteria.

The problem that I encountered dates from the second world war.  What would happen to the British royal family if the country was invaded?  Where would they go?  The government had contingency plans for a last ditch conflict on British soil rather than surrender.  And for morale, the king and his family were to stay in the country as long as possible.  So, it was necessary to plan for a relocation of the government and leading civil servants to a new base, away from London.  With the king close by.

The decision had been taken secretly that the new centre of government would be in the West Midlands, specifically Worcestershire and  Warwickshire.  That area satisfied several criteria; it was away from the coast (and one assumed that an invasion would be by sea and land, rather than by air); there were good transport links from London (rail and road) and also to both Liverpool and Bristol, in case a further evacuation was needed; the BBC had a broadcasting centre at Evesham in Worcestershire; and there were no major cities close by which might be targets for bombers; there were RAF airfields and military training camps; the land was not mountainous.  Also, secretly decided, some of the royal family would be evacuated by sea to Canada if the country fell. 

So, where do we send the king?  He would need a mansion or country house.  It must be in the right area, especially for communication and (possibly) further evacuation.

Now come the extra constraints on the location problem.  First, how many alternative houses do we plan for?   It would be unfortunate if the chosen site was rendered unusable, either through a direct attack, or because of the route taken by the invasion.  What if two choices were unusable?  Having several alternatives means that the actual choice can be left to the last minute depending on circumstances.  And second, we assume that the enemy has made the same analysis of where the government of resistance would be based.  So, the chosen home for the royals must be one that is not immediately obvious to the enemy.  Here comes a bit of game theory.  Enemy and UK both think of obvious places.  Both reject these as "Too obvious".  Enemy and UK both think of less obvious places, and reject these.  Enemy and UK think of even less obvious places.  Now we have a list of - perhaps - twenty sites - and the UK makes a selection from these, including some of the obvious and less obvious ones.  It's a bit of bluff and double-bluff.

Croome Court

Tina and I were visiting Croome Court, in Worcestershire, last week.  Records found there show that it was one of five houses (so there is the number of alternatives) surveyed and provided with emergency food supplies in early 1940.  It is a small country house, close to the Bristol-Birmingham road and railway, and also close to the River Severn - which might (at a pinch) be used for a water-borne evacuation.  There was an RAF airfield nearby at Pershore.

The first choice for the alternative royal residence was Madresfield Court, about 5 miles away as the crow flies.  It wasn't necessary to use it for this purpose, but Croome Court was used by the Queen of the Netherlands and her government in exile. 

I wonder what the civil servants thought when they were given the instructions about this location problem?  You are to choose a number of country houses in Worcestershire and Warwickshire for the royal  family.  How many is up to you, but you must justify the cost.  You are to choose ones which are adequate, but not obvious to an enemy.  Then you are to survey them and provision them.   They didn't have the tools for location modelling that we take for granted.

So far, I have been unable to identify the other three possible houses; Google only turns up Madresfield. 

Models for customer and consumer behaviour

The first article that I ever read about OR carried the title "Models for thinking with".  It mentioned optimisation, and analysis, but concentrated on the essence of creating a model (mathematical or otherwise) of an enterprise, where decisions had to be made.  This affects design and both OR people and engineers need their models for thinking with.  Experience changes designs, and evidence feeds into the models that are used.  Some early motor-cars had their rear doors hinged at the rear.  If the door opened while the car was moving, then the door would swing open, giving no protection for the rear-seat passenger.  One picture of these that I saw recently labelled them "Suicide doors".  A popular British car of the 1960s had door handles which pointed forwards - there were accidents where these gouged the flesh of pedestrians.  In each case, there had been unforeseen situations in the models used for the design.  Early ATM machines gave customers their cash before returning the debit card - and numerous cards were left in the machines as a consequence. 

Purchasing new household equipment exposes people to changes in routine.  Other writers have commented on the difficulties of changing to a new model of a mobile phone, a DVD recorder, or other electronic item.  Purchasers change these at comparatively long intervals, during which time the manufacturers make steady changes and introduce new features.  What should be in the instruction manual (which was probably written by someone who is familiar with the immediately preceding model!)?

We have just bought a new upright freezer; the problem is that our behaviour (lifestyle) has been developed with the old one.  The new one has drawers and no shelves.  We have grown used to freezing food on a shelf, and, once frozen, either moving it  to a drawer, or to one side of the shelf to make room for further food to be frozen.  So we shall have to start freezing food in the spacious fast freeze drawer.  But that is going to mean
either (a) reserving that drawer for fast freezing (wasted space at other times)
or (b) rearranging items in the fast freeze drawer so that items we put in are not in contact with frozen food (inconvenient because it is so deep)

In due time we will adapt our lifestyle - but the model used by the designer for human behaviour with their freezer didn't include the way we use ours.

We have had to adapt our behaviour to the model used by the oven timer on our cooker.  A long time ago, the earliest cooker timers in the UK allowed you to set the start time and the finish time.  The next generation allowed you to set the start time and the duration of the oven being on.  Both of these needed a simple operation to keep the oven on for a while longer.  Our current model asks for the duration and the time to switch off.  Extending the cooking time requires reprogramming the timer, or switching it to manual.  You can see the reasoning in the designer's model for the use of a timer on an oven.  The oven is being used to prepare a meal, so you set the time of the meal and then the cooking time.  How reasonable!  But, that model presupposes that the oven is being set for one item.  What about the person who wants to cook a joint and to add a hot pudding to the oven before the joint is cooked?  What time should you programme to finish, and how long for?  That behaviour wasn't in the mind of the designer.

All of these are reminders that when we use models for thinking with, we must think of as many aspects of the situation as possible, and not assume that everyone behaves in the same way.

Causal correlation or casual correlation

The following story is included in its entirety.  Leaving aside all the effort which went into collecting the data, what does it say?  

It doesn't say that if you asked the local council to rename your street, then your house price would automatically change.  All that it is saying is that there is an interesting relationship between street names and house prices.  The examples given of Upper Phillimore Gardens and Zeus Lane illustrate this;  exchanging the names would have little effect on the prices - because they depend on the location, size, facilities, etc of the properties on each road.

Added to which, I have commented elsewhere on the methods used by estate agents to establish the current value of houses.  Look at the precision of the figures here "the average home is worth £5,740,496."  There are 53 properties in that road, and the algorithm for estimating their value gives a figure correct to the last pound.  Now the properties vary from detached through semi-detached to flats.  So the average is the average of dissimilar properties.  (Adding grapes to oranges and melons to give the average for fruit.)  Presumably their average is the mean.  But is that an appropriate statistic to use, for data which are skewed, and by definition non-negative?

The house that I grew up in was in a road whose name began with R (£223,241).  Most of my postgraduate years I lived in a road starting with S (£228,237)  In Exeter, streets for my three homes have started with F, W and M (£228,489, £231,145, £221,498 respectively)

However, in the same order, those five streets have the following current average property prices:
£403,716  (A village with large houses)
£197,501
£190,002  (Exeter when I was single, where the properties included flats)
£217,555  (Getting married moved me up in status?)
£595,308

So what?  As this blog is about Operational Research, I suppose that the story reminds me that one must ask whether we always ask the right critical questions about our analysis.

Vowel play – street names starting with U have highest av. property values #zooplafacts

April 5, 2013 at 11:44 AM Lawrence Hall Leave a comment

Forget streets with the X-factor, living on a street with a name beginning with the letter ‘U’ could mean your property is worth a lot more, according to Zoopla.co.uk research.
We analysed average house prices on more than three-quarters of a million streets in the UK. The most expensive street beginning with ‘U’ is Upper Phillimore Gardens where the average home is worth £5,740,496.
Average property prices on streets that start with a ‘U’ currently stand at £251,307 – the highest of any letter in the alphabet – and £25,503 more than the current average UK property value of £225,804.
At the other end of the scale, streets beginning with the letter ‘Z’ have the lowest property values, with the average property worth just £180,046 – 20% less than the UK average. One particular example is Zeus Lane in Waterlooville, Hampshire. Despite being named after a Greek god, property values on the street are far from Olympian. The average property value on the street is just £141,278, 37% lower than the national average of £225,804.
Streets beginning with the letters T (£248,008) and O (£244,450) came in second and third respectively in terms of the highest average property values, while those starting with the letters J (£190,802) and A (£211,744) record the second and third lowest property prices.
And vowels beat consonants hands down when it comes to house prices. The average property on a street beginning with a vowel is worth £6,306 (3%) more than a street beginning with a consonant. Street names beginning with a consonant have an average property value of £222,789, compared to £229,095 for those with a vowel.
So, it seems that there may be more to a street name than meets the eye. With a £70,000 difference between the average property price on streets starting with the letters U and Z, and a £6,000 difference on average on streets beginning with vowels and consonants, it is advisable to select your street wisely!

The A-Z (or U-Z!) of property values

Starting Letter	No. of UK Streets	Avg. Property Value
U	3,565	£251,307
T	44,927	£248,008
O	16,358	£244,450
H	53,223	£234,045
C	77,769	£233,873
P	36,065	£233,550
W	50,979	£231,145
F	25,835	£228,489
L	39,563	£228,400
S	71,304	£228,237
B	71,884	£227,105
Q	3,826	£226,824
N	18,475	£225,911
R	31,154	£223,241
M	51,216	£221,498
K	16,728	£221,106
G	33,335	£219,248
I	4,316	£219,125
E	19,216	£218,849
D	25,395	£218,643
Y	2,751	£218,367
V	7,752	£217,240
A	31,333	£211,744
J	5,565	£190,802
Z	180	£180,046

As always, please feel free to share and use this info, all we ask is that you credit the source as Zoopla.co.uk and link to Zoopla.co.uk. Thank you.

The joy of ... academic papers?

Earlier this year, I wrote about Father Geoffrey's journey (here), the account of a piece of research which I had written up for publication.  It is now freely available (OR Insight 26: 140-148, doi:10.1057/ori.2012.16, here or pdf).  Yesterday, copies of the journal issue arrived to subscribers.  This morning, there was an email from one of my oldest friends and colleagues in Operational Research, reading:

Dear David,
I have a confession.  I enjoyed your article.

I suspect that some of that email was written, tongue-in-cheek, to let me know that he had seen it and had read it.  And he was doubtless aware of the old joke that only three people ever read research papers - the author and the two referees.  So it is pleasant to know that at least one person read the paper on the day it appeared. 

However, there is a deeper aspect to the message.  How often do we enjoy an article in our research journals?  I mean research journals, not our professional journals, which should have a lighter style.  Put you hand on your heart and ask "Which papers over my O.R. career have I enjoyed reading?"  For many of us, the answer will be embarrassingly few.  I can think of half a dozen, in each of which the personality of the authors came through, as they wrote about their enthusiasm for the work that they were describing.  And these papers still maintained academic rigour. 

The academic style has been lampooned numerous times; I really enjoyed the spoof reports of an 11 month old girl and her toys (description and "academic" paper) as an example.

How could your next paper or presentation be prepared so that people might "Enjoy" it?