Example analysis of how to implement knapsack algorithm in Java

public class Bag {

  static class Item {// 定义一个物品
    String id; // 物品id
    int size = 0;// 物品所占空间
    int value = 0;// 物品价值

    static Item newItem(String id, int size, int value) {
      Item item = new Item();
      item.id = id;
      item.size = size;
      item.value = value;
      return item;
    }

    public String toString() {
      return this.id;
    }
  }

  static class OkBag { // 定义一个打包方式
    List<Item> Items = new ArrayList<Item>();// 包里的物品集合

    OkBag() {
    }

    int getValue() {// 包中物品的总价值
      int value = 0;
      for (Item item : Items) {
        value += item.value;
      }
      return value;
    };

    int getSize() {// 包中物品的总大小
      int size = 0;
      for (Item item : Items) {
        size += item.size;
      }
      return size;
    };

    public String toString() {
      return String.valueOf(this.getValue()) + " ";
    }
  }

  // 可放入包中的备选物品
  static Item[] sourceItems = { Item.newItem("4号球", 4, 5), Item.newItem("5号球", 5, 6), Item.newItem("6号球", 6, 7) };
  static int bagSize = 10; // 包的空间
  static int itemCount = sourceItems.length; // 物品的数量

  // 保存各种情况下的最优打包方式 第一维度为物品数量从0到itemCount,第二维度为包裹大小从0到bagSize
  static OkBag[][] okBags = new OkBag[itemCount + 1][bagSize + 1];

  static void init() {
    for (int i = 0; i < bagSize + 1; i++) {
      okBags[0][i] = new OkBag();
    }

    for (int i = 0; i < itemCount + 1; i++) {
      okBags[i][0] = new OkBag();
    }
  }

  static void doBag() {
    init();
    for (int iItem = 1; iItem <= itemCount; iItem++) {
      for (int curBagSize = 1; curBagSize <= bagSize; curBagSize++) {
        okBags[iItem][curBagSize] = new OkBag();
        if (sourceItems[iItem - 1].size > curBagSize) {// 当前物品大于包空间.肯定不能放入包中.
          okBags[iItem][curBagSize].Items.addAll(okBags[iItem - 1][curBagSize].Items);
        } else {
          int notIncludeValue = okBags[iItem - 1][curBagSize].getValue();// 不放当前物品包的价值
          int freeSize = curBagSize - sourceItems[iItem - 1].size;// 放当前物品包剩余空间
          int includeValue = sourceItems[iItem - 1].value + okBags[iItem - 1][freeSize].getValue();// 当前物品价值+放了当前物品后剩余包空间能放物品的价值
          if (notIncludeValue < includeValue) {// 放了价值更大就放入.
            okBags[iItem][curBagSize].Items.addAll(okBags[iItem - 1][freeSize].Items);
            okBags[iItem][curBagSize].Items.add(sourceItems[iItem - 1]);
          } else {// 否则不放入当前物品
            okBags[iItem][curBagSize].Items.addAll(okBags[iItem - 1][curBagSize].Items);
          }
        }

      }
    }
  }

  public static void main(String[] args) {
    Bag.doBag();
    for (int i = 0; i < Bag.itemCount + 1; i++) {// 打印所有方案中包含的物品
      for (int j = 0; j < Bag.bagSize + 1; j++) {
        System.out.print(Bag.okBags[i][j].Items);
      }
      System.out.println("");
    }

    for (int i = 0; i < Bag.itemCount + 1; i++) {// 打印所有方案中包的总价值
      for (int j = 0; j < Bag.bagSize + 1; j++) {
        System.out.print(Bag.okBags[i][j]);
      }
      System.out.println("");
    }

    OkBag okBagResult = Bag.okBags[Bag.itemCount][Bag.bagSize];
    System.out.println("最终结果为:" + okBagResult.Items.toString() + okBagResult);

  }

}