A different version of this piece was published back in 2009, in the OR/MS Today magazine.
It is well known that the partition of the Indian subcontinent in 1947 had terrible consequences. Tens of thousands of people died. Millions were displaced and lost their cherished ancestral homes: Muslims left India for Pakistan, and Hindus and Sikhs left Pakistan for India. It was the greatest mass migration in history. But what is less understood is the manner in which the vast numbers of refugees were accommodated and settled into the newly divided regions. The greatest mass migration in history inevitably became the largest resettlement operation in the world.
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It is well known that the partition of the Indian subcontinent in 1947 had terrible consequences. Tens of thousands of people died. Millions were displaced and lost their cherished ancestral homes: Muslims left India for Pakistan, and Hindus and Sikhs left Pakistan for India. It was the greatest mass migration in history. But what is less understood is the manner in which the vast numbers of refugees were accommodated and settled into the newly divided regions. The greatest mass migration in history inevitably became the largest resettlement operation in the world.
How was
this monumental task achieved? That question might take up many books, and
perhaps many have already been written. But we get a glimpse of how
it was done in the Indian side of the Punjab (East Punjab) in Refugees and the Republic a chapter in Ramachandra Guha’s post-independence historical narrative India
after Gandhi.
Guha’s
chapter appealed to me for a different reason. My specialization is the field
of operations
research: the quantitative or optimization methods that are now used
widely in the attempt to make service systems more efficient. The resettlement or land allocation problem set up
by Guha in the chapter seemed to fall squarely in the realm of optimization. I
was curious to know how the reallocation of land had been carried out in practice.
Punjab
was one of the partitioned provinces; the eastern part found itself in India
while the western in Pakistan. A large number of Muslims had left East Punjab
for Pakistan. But there was an even greater influx of Hindus and Sikhs into the
east from Pakistan. Most of these refugees were
farmers. Together they had abandoned 2.7 million hectares of land in Western
Punjab but across the border in India where they now had to make a living only
1.9 million hectares had been left behind by Muslim farmers who had fled the
opposite way. The problem was made more complex by three additional factors:
- Each refugee family had a claim
on how much they had owned prior to emigrating.
- The fertility of the land
differed; there were dry, unirrigated districts as well as lush, irrigated
regions.
- There were demands that
families and neighbors be relocated in the same way as they had been in
West Punjab. If possible entire village communities had to be recreated.
From
the comfort of hindsight – and given how far computing power has grown in the
last 6-7 decades – I can imagine formulating the land allocation problem as a
large scale mathematical
optimization model. The decisions
(the x variables in the problem,
which the model would be solved for) would be how much land to allocate to each
family and where to allocate. The objective,
expressed as a function of the
decisions, would be to minimize the difference between claims and actual
allocations. The constraints would be
equations that expressed limits such as the total land allocated could not
exceed the total land available. There
could be other constraints to ensure that families and neighbors are relocated
together. The mathematical model would also have to capture the spatial aspect,
the variation in fertility and relate them somehow to the allocation decisions.
Even by
today’s standards this is a very difficult optimization problem; it also has
human or qualitative dimensions that are difficult to capture mathematically. The
unenviable task of reallocating land fell upon the Indian government and its
civil service workers. As a first step, they assigned each family of refugee
farmers 4 hectares irrespective of its past holding; they also gave loans to
buy seed and equipment. Viewed from an optimization lens, this 4-acre allotment
is an “initial solution” – a feasible assignment to the decisions (the x’s) to get things going, but very far
from optimal.
As
families began to sustain themselves, applications were invited for them to
claim more land, depending on what they had owned in West Punjab. Within a month,
there were 500,000 claims. These claims were then “verified in open assemblies
consisting of other migrants from the same village. As each claim was read out
by a government official, the assembly approved, amended or rejected it.” Refugees
tended to exaggerate of course, but were deterred by the open assembly method;
if a claim turned out to be false they were punished by a reduction in land.
Sardar
Tarlok Singh of the Indian Civil Service and a graduate of the London School of
Economics led the rehabilitation operation. He used two simple but interesting
rules (we call them heuristics) for
allocating land, and this is where the pragmatism in the whole operation comes
most clearly to light. Though claims had been filed, because of the reduced
acreage, none of the refugees could be assigned as much land as they'd
originally owned. Everybody’s claim had to be reduced by a certain percentage.
Plus, there had to be some way of accounting for the differing fertility of
land.
Sardar
Tarlok Singh came up with two measures, the
standard acre and the graded cut, which dealt
with these issues:
“A standard acre was defined
as that amount of land which could yield ten to eleven maunds of rice. (A maund
is about 40 kilograms.) In the dry, unirrigated districts of the east, four
physical acres were equivalent to one standard acre; but in the lush “canal
colonies” [where irrigation was strong], one physical acre was about equal to
one standard acre. The innovative concept of the standard acre took care of the
variations in soil and climate across the province.
The idea of the graded cut,
meanwhile, helped overcome the large discrepancy between the land left behind
by the refugees and the land now available to them – a gap that was close to
million acres. For the first ten acres of any claim, a cut of 25% was
implemented – thus one got only 7.5 acres instead of ten. For higher claims the
cuts were steeper: 30% between ten and 30 acres, and on upward, so that those
having more than 500 acres were taxed at the rate of 95%.”
With this
rule, there clearly were losers, and the losers, of course, were those who had
once owned huge tracts of land: “The biggest single loser was a woman named
Vidyawati who had inherited land (and lost) her husband’s estate of 11,500
acres spread across thirty-five villages of the Gujranwala and Sialkot
districts. In compensation she was allotted mere 835 acres in a single village
of Karnal.”
It’s unclear what
analysis motivated Tarlok Singh to come up with the specific ranges and the
cuts. It’s possible that the taxing mechanism might have left too much land
unassigned, and many claimants dissatisfied. Or, given that the overall
reduction in total land was about 38 percent (the farmers had left 2.7 million
hectares behind and now were being resettled on 1.7 million hectares), the
taxing may not have been strict enough. The exact details are unknown.
What is known, though, is
that by November 1949, a year and a half after the resettlement began, “Tarlok
Singh had made 250000 allotments distributed equitably across the districts of
East Punjab”. Even the soft constraints, such as settling families and
neighbors together, were met to a large extent, though “the recreation of
entire village communities proved impossible.” The resettlements were so
successful that “by 1950, a depopulated countryside was alive once again.”
Tarlok’s heuristics might have been simple, but they helped solve a complex,
large-scale allotment problem in the aftermath of a traumatic event.
Halfway across the world, in the summer of 1947 — the same year that the partition of the Indian subcontinent took place — George Dantzig conceived the famous Simplex Algorithm. In the next decades the Simplex Algorithm, helped by advances in the computing capability, would provide fast solutions to large linear optimization problems. Each fall I teach the algorithm to graduate students from many disciplines. But in 1947, the Simplex algorithm could only tackle a small version of the classical diet problem: optimally choosing food items for a family to minimize costs while ensuring minimum nutritional needs are met. That particular diet problem had only 9 constraints and 27 variables, but took 120 man-days to solve; worksheets were glued together and spread out like a tablecloth to assist in determining the optimum solution [1].
This puts the enormity of
resettlement problem in perspective. With half a million people making claims –
which means there would be hundreds of thousands of variables and constraints –
even an awareness of Dantzig’s algorithm could not have helped the Indian Civil
Service.
Nearly 7,000 officials
were needed for the resettlement effort; they constituted a refugee city of
their own. The problem occupied them for a period of three years. Imagine the
paperwork and the records that had to be kept and retrieved; imagine the
disputes among the refugees, the flared tempers and the jealousies. But imagine
also the perseverance of everyone involved. It made me think about what it is
exactly that makes certain large scale operations successful and others not.
It’s hard to make generalizations, but one feature seems to be effective
coordination across large groups of people: largely error-free lunch deliveries
by the Dabbawalas of
Mumbai is an example that comes to mind.
Related
notes:
1. Guha
ends the chapter in his book poignantly. The resettlement, Guha says, may have
been successful, but the general sense of loss could not be undone. The
migrating Sikhs had left behind a beloved place of worship, Nankana Sahib, the
birthplace of the founder of their faith, Guru Nanak. Muslims
migrating from East Punjab too had left behind the town of Qadian, the center
of the Ahmadiya sect of Islam; the Ahmadiya mosque was
visible for miles around. Very few Muslims now lived in Qadian, which was full
of Hindu and Sikh refugees. Guha quotes the editor of the Calcutta newspaper
Statesman, who wrote that in both Qadian and Nankana Sahib there was “the conspicuous
dearth of daily worshippers, the aching emptiness, the sense of waiting, of
hope and…of faith fortified by humbling affliction.”
2. The
picture shows a boy at a Delhi refugee camp in 1947. Here is the source.
The largest refugee camp, though, was at Kurukshetra, consisting of nearly
300,000 people. For their entertainment, film projectors were brought in and
Disney specials featuring Mickey Mouse and Donald Duck were screened at night.
It was, as one social worker described it, a “two-hour break from reality”.
References
1. Bazaraa, M., Jarvis, J., and Sherali, H., 2005,
Linear Programming and Network Flows, Wiley 3rd Edition
2. All quoted parts in the piece are from Ramachandra Guha’s India After Gandhi.
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