Ben Davies Blog Research Vita

Let \(\newcommand{\N}{\mathbb{N}}\N=\{1,2,\ldots\}\) be the set of positive integers. A partition of \(n\in\N\) is a way of writing \(n\) as a sum of positive integers, called parts. For example, \(1+2+3\) is a partition of \(6\), with parts \(1\), \(2\), and \(3\). Partitions are unique up to rearrangement: \(1+2+3\) and \(3+2+1\) are the same partition, but \(1+2+3\) and \(3+3\) are different partitions.

This post discusses the following problem:

Let \(n\ge2\) be a positive integer. Find a partition of \(n\) whose parts have maximum product.

For example, the parts in \(1+2+3\) have product \(1\times2\times3=6\), while the parts in \(3+3\) have product \(3\times3=9\). Our goal is to find a product-maximising partition for arbitrary \(n\).

Let \(x_1+x_2+\cdots+x_k\) be a partition of \(n\). If \(x_1=1\) then \(k\ge2\) (since \(n\ge2\)) and $$\begin{align} \prod_{i=1}^kx_i &= 1\times x_2\times\prod_{i=3}^kx_i \\ &< (1+x_2)\times\prod_{i=3}^kx_i \end{align}$$ because the \(x_i\) are strictly positive.1 Thus, replacing the partition \(x_1+x_2+\cdots+x_k\) with \((1+x_2)+x_3+\cdots+x_k\) delivers a greater product. Since the \(x_i\) can be rearranged arbitrarily, it follows that product-maximising partitions contain no parts equal to one. Similarly, if \(x_1>4\) then $$\begin{align} \prod_{i=1}^kx_i &= x_1\times\prod_{i=2}^kx_i \\ &< 3(x_1-3)\times\prod_{i=2}^kx_i, \end{align}$$ so we can obtain a greater product by replacing \(x_1+x_2+\cdots+x_k\) with \(3+(x_1-3)+x_2+\cdots+x_k\). It follows that product-maximising partitions contain no parts greater than four. But \(2\times2=4\) and \(2+2=4\), so we can replace each four with two twos without reducing the parts’ product. Thus, we can obtain a product-maximising partition using only twos and threes. Finally, if a partition contains three twos then we should replace them with two threes, since \(2+2+2=3+3\) but \(2^3=8<9=3^2\).

To summarise, we can obtain a product-maximising partition using only twos and threes, with as many threes as possible. Letting \(n=3q+r\) for some \(q\in\N\cup\{0\}\) and \(r\in\{0,1,2\}\), the maximum product we can obtain is $$P(n)=\begin{cases}3^q&\text{if}\ r=0\\ 2^2\times3^{q-1}&\text{if}\ r=1\\ 2\times3^q&\text{if}\ r=2.\end{cases}$$ We can approximate this solution by relaxing the integrality constraint on the \(x_i\). For any given \(k\), we can find the vector \(x^*\) that solves $$\newcommand{\R}{\mathbb{R}}\max_{x\in\R_+^k}\prod_{i=1}^kx_i\ \text{subject to}\ \sum_{i=1}^kx_i=n \tag{1},$$ where \(\R_+\) is the set of positive real numbers. This vector has \(x_i^*=n/k\) for each \(i\in\{1,2,\ldots,k\}\), so that \(\prod_{i=1}^kx_i^*=(n/k)^k\).2 If there was no integrality constraint on \(k\) then we could maximise \((n/k)^k\) by choosing \(k=n/e\), where \(e\approx2.718\) is Euler’s constant. But \(k\) must be an integer, so we should round it to the nearest integer in whatever direction delivers the greatest value of \((n/k)^k\). Doing so delivers an estimate $$\hat{P}(n)=\max\left\{\left(\frac{n}{\lfloor n/e\rfloor}\right)^{\lfloor n/e\rfloor},\left(\frac{n}{\lceil n/e\rceil}\right)^{\lceil n/e\rceil}\right\}$$ of \(P(n)\), where \(x\mapsto\lfloor x\rfloor\) and \(x\mapsto\lceil x\rceil\) are the floor (“round down”) and ceiling (“round up”) functions.

The table below compares \(P(n)\) and \(\hat{P}(n)\) for various \(n\). Since \(\{2,3\}\subset\mathbb{R}_+\), the partition of \(n\) using twos and as many threes as possible is a feasible, but not necessarily optimal, solution to \((1)\). Thus \(P(n)\le\hat{P}(n)\) for each \(n\ge2\). The multiplicative error \(\hat{P}(n)/P(n)\) grows exponentially with \(n\) because the exponent \(k\in\{\lfloor n/e\rfloor,\lceil n/e\rceil\}\) of \((n/k)^k\) grows (increasingly linearly) with \(n\), amplifying the error in the approximation \(n/k\sim e\) to each part in the partition underlying \(P(n)\).

\(n\) \(P(n)\) \(\hat{P}(n)\) \(\hat{P}(n)/P(n)\)
2 2 2 1.00
3 3 3 1.00
4 4 4 1.00
5 6 6.25 1.04
10 36 39.06 1.09
50 8.61×107 9.70×107 1.13
100 7.41×1015 9.47×1015 1.28
500 3.19×1079 7.66×1079 2.40
1,000 1.01×10159 5.86×10159 5.78

  1. If \(j>k\) then \(\prod_{i=j}^kx_i=1\) by convention. ↩︎

  2. One can derive \(x_i^*=n/k\) using the method of Lagrange multipliers. ↩︎