Olympiad Maths Prep

Track / Stage 9 / 80 of 80 #1960 of 2000

Problem 1960

IMO P2/P5; hard shortlist
Combinatorics Difficulty 9.3 Prove it IMO Shortlisted Problems · IMO

Let kk be a positive integer. The organising committee of a tennis tournament is to schedule the matches for 2k2k players so that every two players play once, each day exactly one match is played, and each player arrives to the tournament site the day of his first match, and departs the day of his last match. For every day a player is present on the tournament, the committee has to pay 1 coin to the hotel. The organisers want to design the schedule so as to minimise the total cost of all players' stays. Determine this minimum cost.

This one wants a proof. Work it on paper, read the official solution, then mark yourself honestly — the ladder only means something if the record is true.

Official solutions — 2

Solution 1

Enumerate the days of the tournament 1,2,,(2k2)1,2, \ldots, \binom{2k}{2}. Let b1b2b2kb_{1} \leqslant b_{2} \leqslant \cdots \leqslant b_{2k} be the days the players arrive to the tournament, arranged in nondecreasing order; similarly, let e1e2ke_{1} \geqslant \cdots \geqslant e_{2k} be the days they depart arranged in nonincreasing order (it may happen that a player arrives on day bib_{i} and departs on day eje_{j}, where iji \neq j). If a player arrives on day bb and departs on day ee, then his stay cost is eb+1e-b+1. Therefore, the total stay cost is
Σ=i=12keii=12kbi+n=i=12k(eibi+1) \Sigma=\sum_{i=1}^{2k} e_{i}-\sum_{i=1}^{2k} b_{i}+n=\sum_{i=1}^{2k}\left(e_{i}-b_{i}+1\right)

Bounding the total cost from below. To this end, estimate ei+1bi+1+1e_{i+1}-b_{i+1}+1. Before day bi+1b_{i+1}, only ii players were present, so at most (i2)\binom{i}{2} matches could be played. Therefore, bi+1(i2)+1b_{i+1} \leqslant \binom{i}{2}+1. Similarly, at most (i2)\binom{i}{2} matches could be played after day ei+1e_{i+1}, so ei(2k2)(i2)e_{i} \geqslant \binom{2k}{2}-\binom{i}{2}. Thus,
ei+1bi+1+1(2k2)2(i2)=k(2k1)i(i1) e_{i+1}-b_{i+1}+1 \geqslant \binom{2k}{2}-2\binom{i}{2}=k(2k-1)-i(i-1)
This lower bound can be improved for i>ki>k: List the ii players who arrived first, and the ii players who departed last; at least 2i2k2i-2k players appear in both lists. The matches between these players were counted twice, though the players in each pair have played only once. Therefore, if i>ki>k, then
ei+1bi+1+1(2k2)2(i2)+(2i2k2)=(2ki)2. e_{i+1}-b_{i+1}+1 \geqslant \binom{2k}{2}-2\binom{i}{2}+\binom{2i-2k}{2}=(2k-i)^{2}.

An optimal tournament. We now describe a schedule in which the lower bounds above are all achieved simultaneously. Split players into two groups XX and YY, each of cardinality kk. Next, partition the schedule into three parts. During the first part, the players from XX arrive one by one, and each newly arrived player immediately plays with everyone already present. During the third part (after all players from XX have already departed) the players from YY depart one by one, each playing with everyone still present just before departing.

In the middle part, everyone from XX should play with everyone from YY. Let S1,S2,,SkS_{1}, S_{2}, \ldots, S_{k} be the players in XX, and let T1,T2,,TkT_{1}, T_{2}, \ldots, T_{k} be the players in YY. Let T1,T2,,TkT_{1}, T_{2}, \ldots, T_{k} arrive in this order; after TjT_{j} arrives, he immediately plays with all the Si,i>jS_{i}, i>j. Afterwards, players SkS_{k}, Sk1,,S1S_{k-1}, \ldots, S_{1} depart in this order; each SiS_{i} plays with all the Tj,ijT_{j}, i \leqslant j, just before his departure, and SkS_{k} departs the day TkT_{k} arrives. For 0sk10 \leqslant s \leqslant k-1, the number of matches played between TksT_{k-s}'s arrival and SksS_{k-s}'s departure is
j=ksk1(kj)+1+j=ksk1(kj+1)=12s(s+1)+1+12s(s+3)=(s+1)2 \sum_{j=k-s}^{k-1}(k-j)+1+\sum_{j=k-s}^{k-1}(k-j+1)=\frac{1}{2} s(s+1)+1+\frac{1}{2} s(s+3)=(s+1)^{2}
Thus, if i>ki>k, then the number of matches that have been played between Tik+1T_{i-k+1}'s arrival, which is bi+1b_{i+1}, and Sik+1S_{i-k+1}'s departure, which is ei+1e_{i+1}, is (2ki)2(2k-i)^{2}; that is, ei+1bi+1+1=(2ki)2e_{i+1}-b_{i+1}+1=(2k-i)^{2}, showing the second lower bound achieved for all i>ki>k.

If iki \leqslant k, then the matches between the ii players present before bi+1b_{i+1} all fall in the first part of the schedule, so there are (i2)\binom{i}{2} such, and bi+1=(i2)+1b_{i+1}=\binom{i}{2}+1. Similarly, after ei+1e_{i+1}, there are ii players left, all (i2)\binom{i}{2} matches now fall in the third part of the schedule, and ei+1=(2k2)(i2)e_{i+1}=\binom{2k}{2}-\binom{i}{2}. The first lower bound is therefore also achieved for all iki \leqslant k.

Consequently, all lower bounds are achieved simultaneously, and the schedule is indeed optimal.

Evaluation. Finally, evaluate the total cost for the optimal schedule:

\begin{aligned}
\Sigma & =\sum_{i=0}^{k}(k(2k-1)-i(i-1))+\sum_{i=k+1}^{2k-1}(2k-i)^{2}=(k+1)k(2k-1)-\sum_{i=0}^{k} i(i-1)+\sum_{j=1}^{k-1} j^{2} \\
& =k(k+1)(2k-1)-k^{2}+\frac{1}{2}k(k+1)=\frac{1}{2}k\left(4k^{2}+k-1\right)
\end{aligned}

Solution 2

Consider any tournament schedule. Label players P1,P2,,P2kP_{1}, P_{2}, \ldots, P_{2k} in order of their arrival, and label them again Q2k,Q2k1,,Q1Q_{2k}, Q_{2k-1}, \ldots, Q_{1} in order of their departure, to define a permutation a1,a2,,a2ka_{1}, a_{2}, \ldots, a_{2k} of 1,2,,2k1,2, \ldots, 2k by Pi=QaiP_{i}=Q_{a_{i}}.

We first describe an optimal tournament for any given permutation a1,a2,,a2ka_{1}, a_{2}, \ldots, a_{2k} of the indices 1,2,,2k1,2, \ldots, 2k. Next, we find an optimal permutation and an optimal tournament.

Optimisation for a fixed a1,,a2ka_{1}, \ldots, a_{2k}. We say that the cost of the match between PiP_{i} and PjP_{j} is the number of players present at the tournament when this match is played. Clearly, the Committee pays for each day the cost of the match of that day. Hence, we are to minimise the total cost of all matches.

Notice that Q2kQ_{2k}'s departure does not precede P2kP_{2k}'s arrival. Hence, the number of players at the tournament monotonically increases (non-strictly) until it reaches 2k2k, and then monotonically decreases (non-strictly). So, the best time to schedule the match between PiP_{i} and PjP_{j} is either when Pmax(i,j)P_{\max (i, j)} arrives, or when Qmax(ai,aj)Q_{\max \left(a_{i}, a_{j}\right)} departs, in which case the cost is min(max(i,j),max(ai,aj))\min \left(\max (i, j), \max \left(a_{i}, a_{j}\right)\right).

Conversely, assuming that i>ji>j, if this match is scheduled between the arrivals of PiP_{i} and Pi+1P_{i+1}, then its cost will be exactly i=max(i,j)i=\max (i, j). Similarly, one can make it cost max(ai,aj)\max \left(a_{i}, a_{j}\right). Obviously, these conditions can all be simultaneously satisfied, so the minimal cost for a fixed sequence a1,a2,,a2ka_{1}, a_{2}, \ldots, a_{2k} is
Σ(a1,,a2k)=1i<j2kmin(max(i,j),max(ai,aj)). \Sigma\left(a_{1}, \ldots, a_{2k}\right)=\sum_{1 \leqslant i<j \leqslant 2k} \min \left(\max (i, j), \max (a_{i}, a_{j})\right) .

Optimising the sequence (ai)\left(a_{i}\right). Optimisation hinges on the lemma below.

Lemma. If aba \leqslant b and cdc \leqslant d, then
min(max(a,x),max(c,y))+min(max(b,x),max(d,y))min(max(a,x),max(d,y))+min(max(b,x),max(c,y)) \begin{aligned} \min (\max (a, x), \max (c, y))+\min (\max (b, x), \max (d, y)) & \\ & \geqslant \min (\max (a, x), \max (d, y))+\min (\max (b, x), \max (c, y)) \end{aligned}

Proof. Write a=max(a,x)max(b,x)=ba^{\prime}=\max (a, x) \leqslant \max (b, x)=b^{\prime} and c=max(c,y)max(d,y)=dc^{\prime}=\max (c, y) \leqslant \max (d, y)=d^{\prime} and check that min(a,c)+min(b,d)min(a,d)+min(b,c)\min \left(a^{\prime}, c^{\prime}\right)+\min \left(b^{\prime}, d^{\prime}\right) \geqslant \min \left(a^{\prime}, d^{\prime}\right)+\min \left(b^{\prime}, c^{\prime}\right).

Consider a permutation a1,a2,,a2ka_{1}, a_{2}, \ldots, a_{2k} such that ai<aja_{i}<a_{j} for some i<ji<j. Swapping aia_{i} and aja_{j} does not change the (i,j)(i, j)th summand in (1), and for {i,j}\ell \notin\{i, j\} the sum of the (i,)(i, \ell)th and the (j,)(j, \ell)th summands does not increase by the Lemma. Hence the optimal value does not increase, but the number of disorders in the permutation increases. This process stops when ai=2k+1ia_{i}=2k+1-i for all ii, so the required minimum is
S(2k,2k1,,1)=1i<j2kmin(max(i,j),max(2k+1i,2k+1j))=1i<j2kmin(j,2k+1i) \begin{aligned} S(2k, 2k-1, \ldots, 1) & =\sum_{1 \leqslant i<j \leqslant 2k} \min (\max (i, j), \max (2k+1-i, 2k+1-j)) \\ & =\sum_{1 \leqslant i<j \leqslant 2k} \min (j, 2k+1-i) \end{aligned}
The latter sum is fairly tractable and yields the stated result; we omit the details.

Source: MathNet, licensed CC-BY-4.0. Statement and solution reproduced as published; topic, difficulty and ordering added by this site.