{ "cells": [ { "cell_type": "markdown", "id": "0932a7d6", "metadata": { "tags": [ "CSP", "medium", "AllDifferent", "Extension", "Cardinality", "academic" ] }, "source": [ "# Problem *Sport Scheduling*" ] }, { "cell_type": "markdown", "id": "4d7ad8e6", "metadata": {}, "source": [ " From [CSPLib (Problem 26)](https://www.csplib.org/Problems/prob026/): The problem is to schedule a tournament of $n$ teams over $n-1$ weeks, with each week divided into $n/2$ periods, and each period divided into two slots indicating the two involved teams (for example, one playing at home, and the other away).\n", "A tournament must satisfy the following three conditions:\n", "- every team plays every other team.\n", "- every team plays once a week;\n", "- every team plays at most twice in the same period over the tournament;" ] }, { "attachments": { "balls.png": { "image/png": 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" } }, "cell_type": "markdown", "id": "ad947cbb", "metadata": {}, "source": [ "Sports Scheduling. Image from [commons.wikimedia.org](https://commons.wikimedia.org/wiki/File:Sports_portal_bar_icon.png) \n", "" ] }, { "cell_type": "markdown", "id": "94a74e89", "metadata": {}, "source": [ "To build a CSP (Constraint Satisfaction Problem) model, we need first to import the library PyCSP$^3$:" ] }, { "cell_type": "code", "execution_count": 1, "id": "b7c3404f", "metadata": {}, "outputs": [], "source": [ "from pycsp3 import *" ] }, { "cell_type": "markdown", "id": "9d5731e7", "metadata": {}, "source": [ "Then, we need some data. Actually, we just need an (even) integer $n$. For example, the value 6." ] }, { "cell_type": "code", "execution_count": 2, "id": "f64937d4", "metadata": {}, "outputs": [], "source": [ "nTeams = 6\n", "nWeeks = nTeams -1\n", "nPeriods = nTeams // 2\n", "nMatches = (nTeams - 1) * nTeams // 2" ] }, { "cell_type": "markdown", "id": "76a32fce", "metadata": {}, "source": [ "We display the value fo the constants, to control them:" ] }, { "cell_type": "code", "execution_count": 3, "id": "aa9e2f54", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Number of periods: 3\n", "Number of matches: 15\n" ] } ], "source": [ "print(\"Number of periods: \", nPeriods)\n", "print(\"Number of matches: \", nMatches)" ] }, { "cell_type": "markdown", "id": "21b14c96", "metadata": {}, "source": [ "Is is interesting to associate a distinct number to each possible match between two teams. We define this function:" ] }, { "cell_type": "code", "execution_count": 4, "id": "127c9d46", "metadata": {}, "outputs": [], "source": [ "def match_number(t1, t2):\n", " return nMatches - ((nTeams - t1) * (nTeams - t1 - 1)) // 2 + (t2 - t1 - 1)" ] }, { "cell_type": "markdown", "id": "49d2fa1a", "metadata": {}, "source": [ "We then compute a table containing information (3-tuples) about all possible matches." ] }, { "cell_type": "code", "execution_count": 5, "id": "0d6e5ee2", "metadata": {}, "outputs": [], "source": [ "table = [(t1, t2, match_number(t1,t2)) for t1, t2 in combinations(range(nTeams), 2)]" ] }, { "cell_type": "markdown", "id": "68f1e1f3", "metadata": {}, "source": [ "We print the table to control it. " ] }, { "cell_type": "code", "execution_count": 6, "id": "ad877b19", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[(0, 1, 0), (0, 2, 1), (0, 3, 2), (0, 4, 3), (0, 5, 4), (1, 2, 5), (1, 3, 6), (1, 4, 7), (1, 5, 8), (2, 3, 9), (2, 4, 10), (2, 5, 11), (3, 4, 12), (3, 5, 13), (4, 5, 14)]\n" ] } ], "source": [ "print(table)" ] }, { "cell_type": "markdown", "id": "199aec8b", "metadata": {}, "source": [ "Note that we do not pay attention to the fact that one team is playing at home and the other away. By construction, any match with number k corresponds to a 3 -tuple (i,j,k) with systematically $i < j$. So, what is recorded in the table is basically the identification of the two teams involved in any match (but not the site where they play). " ] }, { "cell_type": "markdown", "id": "f74367d2", "metadata": {}, "source": [ "We gently start our CSP model with a two-dimensional array $m$ of $5 \\times 3$ variables. This will allow us to represent the number of the match to be played at any week w and any period p." ] }, { "cell_type": "code", "execution_count": 7, "id": "34994c17", "metadata": {}, "outputs": [], "source": [ "# m[w][p] is the number of the match at week w and period p\n", "m = VarArray(size=[nWeeks, nPeriods], dom=range(nMatches))" ] }, { "cell_type": "markdown", "id": "5e8b1031", "metadata": {}, "source": [ "We can display (the structure of) this array as well as the domain of the involved variables." ] }, { "cell_type": "code", "execution_count": 8, "id": "7ace4a64", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Array of variable m: [\n", " [m[0][0], m[0][1], m[0][2]]\n", " [m[1][0], m[1][1], m[1][2]]\n", " [m[2][0], m[2][1], m[2][2]]\n", " [m[3][0], m[3][1], m[3][2]]\n", " [m[4][0], m[4][1], m[4][2]]\n", "]\n", "Domain of any variable in m: 0..14\n" ] } ], "source": [ "print(\"Array of variable m: \", m)\n", "print(\"Domain of any variable in m: \", m[0][0].dom)" ] }, { "cell_type": "markdown", "id": "903a259b", "metadata": {}, "source": [ "Concerning the constraints, we first post a constraint *AllDifferent*." ] }, { "cell_type": "code", "execution_count": 9, "id": "a4d84c01", "metadata": {}, "outputs": [], "source": [ "satisfy(\n", " # all matches are different (no team can play twice against another team)\n", " AllDifferent(m)\n", ");" ] }, { "cell_type": "markdown", "id": "4863c5fe", "metadata": {}, "source": [ "Interestingly, by calling the function *solve()*, we can check that the problem is satisfiable (SAT). We can also display the values of variables in $m$. Here, we call the function *values()* that collects the values assigned to a specified list of variables." ] }, { "cell_type": "code", "execution_count": 10, "id": "e7e811e6", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[\n", " [0, 1, 2]\n", " [3, 4, 5]\n", " [6, 7, 8]\n", " [9, 10, 11]\n", " [12, 13, 14]\n", "]\n" ] } ], "source": [ "if solve() is SAT:\n", " print(values(m))" ] }, { "cell_type": "markdown", "id": "775cd7cc", "metadata": {}, "source": [ "In that \"solution\", one can see that the first condition (every team plays every other team) in the statement of the problem is respected, but not the others (when observing the teams playing each week by looking at the correspondances given in the table)." ] }, { "cell_type": "markdown", "id": "ec26247f", "metadata": {}, "source": [ "Actually, we need to identify the teams involved in the matches. This is why we introduce 2 two-dimensional arrays $x$ and $y$ of $5 \\times 3$ variables." ] }, { "cell_type": "code", "execution_count": 11, "id": "4c749ad4", "metadata": {}, "outputs": [], "source": [ "# x[w][p] is the first team for the match at week w and period p\n", "x = VarArray(size=[nWeeks, nPeriods], dom=range(nTeams))\n", "\n", "# y[w][p] is the second team for the match at week w and period p\n", "y = VarArray(size=[nWeeks, nPeriods], dom=range(nTeams))" ] }, { "cell_type": "markdown", "id": "a336cdfb", "metadata": {}, "source": [ "To make the connection between the matches and the teams, we post a group of constraints *Extension*." ] }, { "cell_type": "code", "execution_count": 12, "id": "51a5ceac", "metadata": {}, "outputs": [], "source": [ "satisfy(\n", " # linking variables through ternary table constraints\n", " (x[w][p], y[w][p], m[w][p]) in table for w in range(nWeeks) for p in range(nPeriods)\n", ");" ] }, { "cell_type": "markdown", "id": "65ec4a5b", "metadata": {}, "source": [ "We can display the internal representation of the posted constraints; this way, although a little bit technical, we can check that the constraints are correctly posted. Here, we just display the 3 last posted constraints." ] }, { "cell_type": "code", "execution_count": 13, "id": "32ca4a87", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "extension(list:[x[4][0], y[4][0], m[4][0]], supports:(0,1,0)(0,2,1)(0,3,2)(0,4,3)(0,5,4)(1,2,5)(1,3,6)(1,4,7)(1,5,8)(2,3,9)(2,4,10)(2,5,11)(3,4,12)(3,5,13)(4,5,14))\n", "extension(list:[x[4][1], y[4][1], m[4][1]], supports:(0,1,0)(0,2,1)(0,3,2)(0,4,3)(0,5,4)(1,2,5)(1,3,6)(1,4,7)(1,5,8)(2,3,9)(2,4,10)(2,5,11)(3,4,12)(3,5,13)(4,5,14))\n", "extension(list:[x[4][2], y[4][2], m[4][2]], supports:(0,1,0)(0,2,1)(0,3,2)(0,4,3)(0,5,4)(1,2,5)(1,3,6)(1,4,7)(1,5,8)(2,3,9)(2,4,10)(2,5,11)(3,4,12)(3,5,13)(4,5,14))\n" ] } ], "source": [ "print(posted()[-3:])" ] }, { "cell_type": "markdown", "id": "9aefd545", "metadata": {}, "source": [ "We can run again the solver." ] }, { "cell_type": "code", "execution_count": 14, "id": "6b751133", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[\n", " [0, 1, 2]\n", " [3, 4, 5]\n", " [6, 7, 8]\n", " [9, 10, 11]\n", " [12, 13, 14]\n", "]\n", "Matches at Week 0: [(0, 1), (0, 2), (0, 3)]\n", "Matches at Week 1: [(0, 4), (0, 5), (1, 2)]\n", "Matches at Week 2: [(1, 3), (1, 4), (1, 5)]\n", "Matches at Week 3: [(2, 3), (2, 4), (2, 5)]\n", "Matches at Week 4: [(3, 4), (3, 5), (4, 5)]\n" ] } ], "source": [ "if solve() is SAT:\n", " print(values(m))\n", " for w in range(nWeeks):\n", " print(f\"Matches at Week {w}: {[(x[w][p].value,y[w][p].value) for p in range(nPeriods)]}\")\n", " " ] }, { "cell_type": "markdown", "id": "8f8f5ada", "metadata": {}, "source": [ "The solution is always the same, but we are now in a position to post constraints so as to respect the second and third conditions in the statement of the problem." ] }, { "cell_type": "markdown", "id": "ddba62b5", "metadata": {}, "source": [ "We start with the second condition in the statement of the problem:" ] }, { "cell_type": "code", "execution_count": 15, "id": "3fad733b", "metadata": {}, "outputs": [], "source": [ "satisfy(\n", " # each week, all teams are different (each team plays each week)\n", " AllDifferent(x[w] + y[w]) for w in range(nWeeks)\n", ");" ] }, { "cell_type": "markdown", "id": "8fbb5f92", "metadata": {}, "source": [ "By calling *posted(-1)* we can get the constraints that have been posted during the last call to *satisfy()*." ] }, { "cell_type": "code", "execution_count": 16, "id": "a5cbf644", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "allDifferent(list:[x[0][0], x[0][1], x[0][2], y[0][0], y[0][1], y[0][2]])\n", "allDifferent(list:[x[1][0], x[1][1], x[1][2], y[1][0], y[1][1], y[1][2]])\n", "allDifferent(list:[x[2][0], x[2][1], x[2][2], y[2][0], y[2][1], y[2][2]])\n", "allDifferent(list:[x[3][0], x[3][1], x[3][2], y[3][0], y[3][1], y[3][2]])\n", "allDifferent(list:[x[4][0], x[4][1], x[4][2], y[4][0], y[4][1], y[4][2]])\n" ] } ], "source": [ "print(posted(-1))" ] }, { "cell_type": "markdown", "id": "dc027a04", "metadata": {}, "source": [ "We can run the solver." ] }, { "cell_type": "code", "execution_count": 17, "id": "0c274032", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Matches at Week 0: [(0, 1), (2, 3), (4, 5)]\n", "Matches at Week 1: [(0, 2), (1, 4), (3, 5)]\n", "Matches at Week 2: [(0, 3), (1, 5), (2, 4)]\n", "Matches at Week 3: [(0, 4), (1, 3), (2, 5)]\n", "Matches at Week 4: [(0, 5), (1, 2), (3, 4)]\n" ] } ], "source": [ "if solve() is SAT:\n", " for w in range(nWeeks):\n", " print(f\"Matches at Week {w}: {[(x[w][p].value,y[w][p].value) for p in range(nPeriods)]}\")" ] }, { "cell_type": "markdown", "id": "65ecc308", "metadata": {}, "source": [ "This is better." ] }, { "cell_type": "markdown", "id": "66c13100", "metadata": {}, "source": [ "Finally, we impose the third condition in the statement of the problem by posting a group of constraints *Cardinality*." ] }, { "cell_type": "code", "execution_count": 18, "id": "53570db8", "metadata": {}, "outputs": [], "source": [ "satisfy(\n", " # each team plays at most two times in each period\n", " Cardinality(x[:, p] + y[:, p], occurrences={t: range(1, 3) for t in range(nTeams)}) for p in range(nPeriods)\n", ");" ] }, { "cell_type": "markdown", "id": "88a70608", "metadata": {}, "source": [ "We can control the posted constraints." ] }, { "cell_type": "code", "execution_count": 19, "id": "b3957a99", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "cardinality(list:[x[0][0], x[1][0], x[2][0], x[3][0], x[4][0], y[0][0], y[1][0], y[2][0], y[3][0], y[4][0]], values:[0, 1, 2, 3, 4, 5], occurs:[1..2, 1..2, 1..2, 1..2, 1..2, 1..2])\n", "cardinality(list:[x[0][1], x[1][1], x[2][1], x[3][1], x[4][1], y[0][1], y[1][1], y[2][1], y[3][1], y[4][1]], values:[0, 1, 2, 3, 4, 5], occurs:[1..2, 1..2, 1..2, 1..2, 1..2, 1..2])\n", "cardinality(list:[x[0][2], x[1][2], x[2][2], x[3][2], x[4][2], y[0][2], y[1][2], y[2][2], y[3][2], y[4][2]], values:[0, 1, 2, 3, 4, 5], occurs:[1..2, 1..2, 1..2, 1..2, 1..2, 1..2])\n" ] } ], "source": [ "print(posted(-1))" ] }, { "cell_type": "markdown", "id": "83b65bd8", "metadata": {}, "source": [ "We can run the solver." ] }, { "cell_type": "code", "execution_count": 20, "id": "f19c0378", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Matches at Week 0: [(0, 1), (2, 3), (4, 5)]\n", "Matches at Week 1: [(0, 2), (1, 4), (3, 5)]\n", "Matches at Week 2: [(1, 5), (2, 4), (0, 3)]\n", "Matches at Week 3: [(2, 5), (1, 3), (0, 4)]\n", "Matches at Week 4: [(3, 4), (0, 5), (1, 2)]\n" ] } ], "source": [ "if solve() is SAT:\n", " for w in range(nWeeks):\n", " print(f\"Matches at Week {w}: {[(x[w][p].value,y[w][p].value) for p in range(nPeriods)]}\")" ] }, { "cell_type": "markdown", "id": "b57768ec", "metadata": {}, "source": [ "Athough not shown here, it is possible to add some symmetry-breaking constraints, and also to reason with a dummy week (to make stronger the constraints *Cardinality*)." ] }, { "cell_type": "markdown", "id": "a997c106", "metadata": {}, "source": [ "Finally, we give below the model in one piece. Here the data is expected to be given by the user (in a command line)." ] }, { "cell_type": "raw", "id": "94b9e69d", "metadata": { "raw_mimetype": "text/x-python" }, "source": [ "from pycsp3 import *\n", "\n", "nTeams = data or 8\n", "nWeeks, nPeriods, nMatches = nTeams - 1, nTeams // 2, (nTeams - 1) * nTeams // 2\n", "\n", "\n", "def match_number(t1, t2):\n", " return nMatches - ((nTeams - t1) * (nTeams - t1 - 1)) // 2 + (t2 - t1 - 1)\n", "\n", "\n", "table = {(t1, t2, match_number(t1, t2)) for t1, t2 in combinations(range(nTeams), 2)}\n", "\n", "# m[w][p] is the number of the match at week w and period p\n", "m = VarArray(size=[nWeeks, nPeriods], dom=range(nMatches))\n", "\n", "# x[w][p] is the first team for the match at week w and period p\n", "x = VarArray(size=[nWeeks, nPeriods], dom=range(nTeams))\n", "\n", "# y[w][p] is the second team for the match at week w and period p\n", "y = VarArray(size=[nWeeks, nPeriods], dom=range(nTeams))\n", "\n", "satisfy(\n", " # all matches are different (no team can play twice against another team)\n", " AllDifferent(m),\n", "\n", " # linking variables through ternary table constraints\n", " [(x[w][p], y[w][p], m[w][p]) in table for w in range(nWeeks) for p in range(nPeriods)],\n", "\n", " # each week, all teams are different (each team plays each week)\n", " [AllDifferent(x[w] + y[w]) for w in range(nWeeks)],\n", "\n", " # each team plays at most two times in each period\n", " [Cardinality(x[:, p] + y[:, p], occurrences={t: range(1, 3) for t in range(nTeams)}) \n", " for p in range(nPeriods)],\n", ")" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.12" } }, "nbformat": 4, "nbformat_minor": 5 }