Exemple #1
0
        public void TestMethodGreedy()
        {
            //Act
            //Note: KPGreedyAlg.Solve() is returning Tuple<int[], int>.
            //Note: Same test cases as before but were testing the greedy algorithm instead.
            //Obviously, the greedy algorithm will return a different answer.
            var t1 = KPGreedyAlg.Solve(new int[0], new int[0], 0, 0);
            var t2 = KPGreedyAlg.Solve(new int[2] {
                2, 3
            }, new int[2] {
                3, 4
            }, 0, 2);
            var t3 = KPGreedyAlg.Solve(new int[0], new int[0], 3, 0);
            var t4 = KPGreedyAlg.Solve(new int[1] {
                3
            }, new int[1] {
                2
            }, 3, 1);
            var t5 = KPGreedyAlg.Solve(new int[1] {
                3
            }, new int[1] {
                2
            }, 1, 1);

            var t6 = KPGreedyAlg.Solve(
                new int[6] {
                10, 12, 3, 7, 20, 7
            },
                new int[6] {
                3, 6, 2, 4, 13, 1
            }, 15, 6);
            var t7 = KPGreedyAlg.Solve(
                new int[7] {
                4, 7, 1, 9, 3, 7, 10
            },
                new int[7] {
                2, 3, 9, 1, 3, 7, 6
            }, 25, 7);
            var t8 = KPGreedyAlg.Solve(
                new int[6] {
                1, 2, 4, 2, 11, 8
            },
                new int[6] {
                1, 2, 2, 6, 4, 3
            }, 10, 6);
            var t9 = KPGreedyAlg.Solve(
                new int[7] {
                2, 6, 2, 7, 11, 12, 1000
            },
                new int[7] {
                5, 15, 1, 3, 8, 5, 30
            }, 30, 7);
            var t10 = KPGreedyAlg.Solve(
                new int[10] {
                1, 2, 4, 7, 2, 9, 6, 7, 10, 15
            },
                new int[10] {
                2, 3, 5, 2, 8, 4, 3, 2, 9, 15
            }, 25, 10);
            var t11 = KPGreedyAlg.Solve(
                new int[5] {
                4, 6, 1, 9, 15
            },
                new int[5] {
                3, 2, 11, 4, 7
            }, 10, 5);
            var t12 = KPGreedyAlg.Solve(
                new int[5] {
                1, 2, 3, 4, 100
            },
                new int[5] {
                5, 5, 5, 5, 5
            }, 5, 5);
            var t13 = KPGreedyAlg.Solve(
                new int[10] {
                5, 8, 5, 3, 16, 8, 100, 1, 6, 7
            },
                new int[10] {
                2, 3, 8, 2, 4, 8, 16, 15, 2, 3
            }, 15, 10);
            var t14 = KPGreedyAlg.Solve(
                new int[6] {
                10, 10, 10, 10, 10, 10
            },
                new int[6] {
                3, 3, 3, 3, 3, 3
            }, 18, 6);
            var t15 = KPGreedyAlg.Solve(
                new int[6] {
                1, 2, 3, 6, 3, 4
            },
                new int[6] {
                200, 500, 400, 350, 300, 300
            }, 1000, 6);
            var t16 = KPGreedyAlg.Solve(
                new int[10] {
                19, 29, 4, 16, 24, 4, 17, 6, 34, 14
            },
                new int[10] {
                14, 20, 4, 15, 17, 3, 17, 6, 25, 25
            }, 100, 10);
            var t17 = KPGreedyAlg.Solve(
                new int[10] {
                8, 7, 20, 16, 8, 26, 8, 4, 18, 6
            },
                new int[10] {
                9, 8, 15, 15, 13, 20, 6, 3, 19, 11
            }, 100, 10);

            //Assert
            Assert.AreEqual(0, t1.Item2);
            Assert.AreEqual(0, t2.Item2);
            Assert.AreEqual(0, t3.Item2);
            Assert.AreEqual(3, t4.Item2);
            Assert.AreEqual(0, t5.Item2);

            Assert.AreEqual(36, t6.Item2); //Optimal
            CollectionAssert.AreEqual(new int[6] {
                1, 1, 0, 1, 0, 1
            }, t6.Item1);

            Assert.AreEqual(40, t7.Item2); //Optimal
            CollectionAssert.AreEqual(new int[7] {
                1, 1, 0, 1, 1, 1, 1
            }, t7.Item1);

            Assert.AreEqual(24, t8.Item2); //Optimal
            CollectionAssert.AreEqual(new int[6] {
                1, 0, 1, 0, 1, 1
            }, t8.Item1);

            Assert.AreEqual(1000, t9.Item2); //Optimal
            CollectionAssert.AreEqual(new int[7] {
                0, 0, 0, 0, 0, 0, 1
            }, t9.Item1);

            Assert.AreEqual(43, t10.Item2); //Optimal
            CollectionAssert.AreEqual(new int[10] {
                0, 0, 1, 1, 0, 1, 1, 1, 1, 0
            }, t10.Item1);

            Assert.AreEqual(19, t11.Item2); //Not Optimal, Off by 2
            CollectionAssert.AreEqual(new int[5] {
                1, 1, 0, 1, 0
            }, t11.Item1);

            Assert.AreEqual(100, t12.Item2); //Optimal
            CollectionAssert.AreEqual(new int[5] {
                0, 0, 0, 0, 1
            }, t12.Item1);

            Assert.AreEqual(42, t13.Item2);  //Optimal
            CollectionAssert.AreEqual(new int[10] {
                1, 1, 0, 0, 1, 0, 0, 0, 1, 1
            }, t13.Item1);

            Assert.AreEqual(60, t14.Item2); //Optimal
            CollectionAssert.AreEqual(new int[6] {
                1, 1, 1, 1, 1, 1
            }, t14.Item1);

            Assert.AreEqual(13, t15.Item2); //Optimal
            CollectionAssert.AreEqual(new int[6] {
                0, 0, 0, 1, 1, 1
            }, t15.Item1);

            Assert.AreEqual(130, t16.Item2); //Not Optimal, Off by 2
            CollectionAssert.AreEqual(new int[10] {
                1, 1, 1, 1, 1, 1, 0, 0, 1, 0
            }, t16.Item1);

            Assert.AreEqual(107, t17.Item2); //Not Optimal, Off by 1
            CollectionAssert.AreEqual(new int[10] {
                1, 1, 1, 1, 0, 1, 1, 1, 1, 0
            }, t17.Item1);
        }
Exemple #2
0
        static void Main(string[] args)
        {
            //Vars
            long worstCaseTime = 0;
            long avgCaseTime   = 0;
            long bestCaseTime  = 0;
            long capAvg        = 0;
            int  numItems;
            int  numberOfItemsIncluded = 0;

            double             percentOfItemsIncluded = 0.0;
            Stopwatch          sw = new Stopwatch();
            Tuple <int[], int> solution;

            //Prompt user for number of problems
            Console.Write("How many problems? ");
            numItems = Convert.ToInt32(Console.ReadLine());

            Console.WriteLine("Generating Items.");

            //Generate items
            List <string>        linesOfFile = new List <string>(File.ReadAllLines("..//Problems//PROBLEM_SIZE_5.txt"));
            Tuple <int[], int[]> problem     = ItemPicker.PickItems(linesOfFile, numItems);

            Console.WriteLine("Done Generating Items. Doing WC Time.");

            //Get Worst Case Time
            //Note: Cap = 8_000_000_000 so everything will fit in knapsack
            sw.Start();
            KPGreedyAlg.Solve(problem.Item2, problem.Item1, 8_000_000_000, numItems);
            sw.Stop();

            worstCaseTime = sw.ElapsedMilliseconds;
            sw.Reset();

            Console.WriteLine("Done. Doing BC Time.");

            //Get Best Case Time
            //Note: Cap = 0 so nothing will fit in knapsack
            sw.Start();
            KPGreedyAlg.Solve(problem.Item2, problem.Item1, 0, numItems);
            sw.Stop();

            bestCaseTime = sw.ElapsedMilliseconds;
            sw.Reset();

            Console.WriteLine("Done. Doing AVG Case time.");

            //Get Average Case Time
            capAvg = numItems * 25;

            sw.Start();
            KPGreedyAlg.Solve(problem.Item2, problem.Item1, capAvg, numItems);
            sw.Stop();

            avgCaseTime = sw.ElapsedMilliseconds;

            Console.WriteLine("Done. Wrapping up.");

            //Calculate percentage of items included for average case
            solution = KPGreedyAlg.Solve(problem.Item2, problem.Item1, capAvg, numItems);

            for (int i = 0; i < solution.Item1.Length; i++)
            {
                if (solution.Item1[i] == 1)
                {
                    ++numberOfItemsIncluded;
                }
            }

            percentOfItemsIncluded = (Convert.ToDouble(numberOfItemsIncluded)) / numItems;

            //Display results on screen
            Console.WriteLine($"Number of Items: {numItems}");
            Console.WriteLine($"Worst Case Time: {worstCaseTime}");
            Console.WriteLine($"Average Case Time: {avgCaseTime}");
            Console.WriteLine($"Best Case Time: {bestCaseTime}");
            Console.WriteLine($"Average Capacity: {capAvg}");
            Console.WriteLine($"Percent Included: {percentOfItemsIncluded}");
            Console.WriteLine($"Number of Items Included: {numberOfItemsIncluded}");
            Console.ReadLine();
        }