123 lines
3.7 KiB
C#
123 lines
3.7 KiB
C#
//
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// Copyright 2012 Hakan Kjellerstrand
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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using System;
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using System.Linq;
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using System.Collections;
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using System.Collections.Generic;
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using Google.OrTools.ConstraintSolver;
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public class SkiAssignment
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{
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/**
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*
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* Ski assignment in Google CP Solver.
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*
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* From Jeffrey Lee Hellrung, Jr.:
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* PIC 60, Fall 2008 Final Review, December 12, 2008
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* http://www.math.ucla.edu/~jhellrun/course_files/Fall%25202008/PIC%252060%2520-%2520Data%2520Structures%2520and%2520Algorithms/final_review.pdf
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* """
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* 5. Ski Optimization! Your job at Snapple is pleasant but in the winter
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* you've decided to become a ski bum. You've hooked up with the Mount
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* Baldy Ski Resort. They'll let you ski all winter for free in exchange
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* for helping their ski rental shop with an algorithm to assign skis to
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* skiers. Ideally, each skier should obtain a pair of skis whose height
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* matches his or her own height exactly. Unfortunately, this is generally
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* not possible. We define the disparity between a skier and his or her
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* skis to be the absolute value of the difference between the height of
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* the skier and the pair of skis. Our objective is to find an assignment
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* of skis to skiers that minimizes the sum of the disparities.
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* ...
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* Illustrate your algorithm by explicitly filling out the A[i, j] table
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* for the following sample data:
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* - Ski heights : 1, 2, 5, 7, 13, 21.
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* - Skier heights: 3, 4, 7, 11, 18.
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* """
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*
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* Also see http://www.hakank.org/or-tools/ski_assignment.py
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*
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*/
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private static void Solve()
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{
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Solver solver = new Solver("SkiAssignment");
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//
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// Data
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//
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int num_skis = 6;
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int num_skiers = 5;
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int[] ski_heights = {1, 2, 5, 7, 13, 21};
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int[] skier_heights = {3, 4, 7, 11, 18};
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//
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// Decision variables
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//
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IntVar[] x = solver.MakeIntVarArray(num_skiers, 0, num_skis-1, "x");
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//
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// Constraints
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//
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solver.Add(x.AllDifferent());
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IntVar[] z_tmp = new IntVar[num_skiers];
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for(int i = 0; i < num_skiers; i++) {
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z_tmp[i] = (ski_heights.Element(x[i])-skier_heights[i]).Abs().Var();
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}
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// IntVar z = solver.MakeIntVar(0, ski_heights.Sum(), "z");
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// solver.Add(z_tmp.Sum() == z);
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// The direct cast from IntExpr to IntVar is potentially faster than
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// the above code.
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IntVar z = z_tmp.Sum().VarWithName("z");
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//
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// Objective
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//
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OptimizeVar obj = z.Minimize(1);
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//
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// Search
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//
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DecisionBuilder db = solver.MakePhase(x,
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Solver.CHOOSE_FIRST_UNBOUND,
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Solver.INT_VALUE_DEFAULT);
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solver.NewSearch(db, obj);
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while (solver.NextSolution()) {
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Console.Write("z: {0} x: ", z.Value());
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for(int i = 0; i < num_skiers; i++) {
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Console.Write(x[i].Value() + " ");
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}
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Console.WriteLine();
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}
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Console.WriteLine("\nSolutions: {0}", solver.Solutions());
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Console.WriteLine("WallTime: {0}ms", solver.WallTime());
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Console.WriteLine("Failures: {0}", solver.Failures());
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Console.WriteLine("Branches: {0} ", solver.Branches());
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solver.EndSearch();
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}
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public static void Main(String[] args)
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{
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Solve();
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}
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}
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