Optimizing Fair Distribution of Pooled Funds among Debtors

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In summary, the conversation discusses a mathematical problem involving different amounts of money owed to different people and a fund to pay them. The goal is to determine how much money should be given to each person so that the total dollar losses for each person are equal. The solution involves calculating the total owed, subtracting the pooled funds, dividing the result by the number of people, and then giving each person the amount owed minus that result. This can be done efficiently on paper or with a computer.
  • #1
mrcleanhands
Firstly, I'm not even sure how to frame this mathematically, but I'd be curious to know what kind of problem it is and what kind of subjects within maths it requires to be able to solve it.

Here's my problem--
I've set it up in excel to help you visualise it.
sss.png

There is a different amount of money owed to different people (Amounts Owed). There is a fund which'll be used to pay out those people (Pooled funds). The pooled funds do not equal the total amount owed. If I divide the amount of pooled funds by 4 and hand it out to each person evenly, the dollar loss amounts will be uneven (since each person is owed a different amount). What I'm trying to do is solve for values highlighted green (how much money is given to each person) such that the total dollar losses for each person will equal (that red column).

Is there some way to do this on paper very efficiently, or is it only a problem for the computer?
 

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  • #2
1) Calculate the total owed.
2) Subtract the total pooled funds from that.
3) Divide the result by the number of people and label it $x. (That tells you how much short the pooled funds are per person.)
4) Give each person the amount owed minus $x.

Then each person will get what he is owed minus the same amount, $x.
 
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  • #3
Just divide the total amount that you're short by 4, and subtract that from the amount owned for every person.
 

Related to Optimizing Fair Distribution of Pooled Funds among Debtors

What is an optimisation problem?

An optimisation problem is a type of mathematical problem that involves finding the best possible solution to a given set of constraints. It involves maximizing or minimizing an objective function, while satisfying certain constraints.

What are the different types of optimisation problems?

There are two main types of optimisation problems: linear and nonlinear. Linear optimisation problems involve linear functions and can be solved using linear programming techniques. Nonlinear optimisation problems involve nonlinear functions and require more complex methods to solve.

What are the steps involved in solving an optimisation problem?

The steps involved in solving an optimisation problem include: defining the problem, identifying the objective function and constraints, formulating the problem as a mathematical model, finding the feasible region, and using optimization techniques to find the optimal solution.

What are some common techniques used to solve optimisation problems?

Some common techniques used to solve optimisation problems include: linear programming, nonlinear programming, dynamic programming, simulated annealing, and genetic algorithms. The choice of technique depends on the type of problem and the complexity of the objective function and constraints.

What are some real-world applications of optimisation problems?

Optimisation problems have a wide range of applications in various fields such as engineering, economics, finance, logistics, and computer science. Some examples include production planning, resource allocation, portfolio optimization, and route optimization for transportation.

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