feat(Go-Tool)： 添加求背包问题最优解三种方式(KnapsackOptimizationUtil.go)及其单测类，添加求背包问题最优解过程路径(KnapsackSearchAnswerUtil.go)及其单测类.添加背包问题的readme相关说明

test/KnapsackOptimizationTest/KnapsackOptimizationUtil_test.go

@@ -0,0 +1,51 @@
+/*
+ *  @Author : huangzj
+ *  @Time : 2020/7/31 15:35
+ *  @Description：背包最优问题工具类
+ *  基本场景：给定n个重量为w1w 1，w2w 2 ,w3w 3 ,…,wnw n ，价值为v1v 1 ,v2v 2 ,v3v 3 ,…,vnv n 的物品和容量为CC的背包，求这个物品中一个最有价值的子集，使得在满足背包的容量的前提下，包内的总价值最大
+ *  参考地址：https://blog.csdn.net/chanmufeng/article/details/82955730
+ */
+
+package KnapsackOptimizationTest
+
+import (
+	"Go-Tool/util/KnapsackOptimization"
+	"fmt"
+	"testing"
+)
+
+func TestKnapsackOptimizationUtil(t *testing.T) {
+	bagItem := make([]*KnapsackOptimization.BagItem, 0)
+	bagItem = append(bagItem, &KnapsackOptimization.BagItem{
+		Value:  3,
+		Weight: 2,
+	})
+	bagItem = append(bagItem, &KnapsackOptimization.BagItem{
+		Value:  3,
+		Weight: 3,
+	})
+	bagItem = append(bagItem, &KnapsackOptimization.BagItem{
+		Value:  4,
+		Weight: 4,
+	})
+	bagItem = append(bagItem, &KnapsackOptimization.BagItem{
+		Value:  5,
+		Weight: 5,
+	})
+	bagItem = append(bagItem, &KnapsackOptimization.BagItem{
+		Value:  6,
+		Weight: 2,
+	})
+	bagItem = append(bagItem, &KnapsackOptimization.BagItem{
+		Value:  7,
+		Weight: 2,
+	})
+	cmd := KnapsackOptimization.NewKnapsackOptimization(bagItem, 12)
+	cmd1 := KnapsackOptimization.NewKnapsackOptimization(bagItem, 12)
+	cmd2 := KnapsackOptimization.NewKnapsackOptimization(bagItem, 12)
+	fmt.Print(cmd.OptimizePackageByRecursion()) //通过递归解背包问题
+
+	fmt.Println(cmd1.KnapsackCycle()) //通过逆序解背包问题.
+
+	fmt.Println(cmd2.KnapsackCycleSimple()) //通过一维数组来解决背包问题
+}

test/KnapsackOptimizationTest/KnapsackSearchAnswerUtil_test.go

@@ -0,0 +1,46 @@
+/*
+ *  @Author : huangzj
+ *  @Time : 2020/8/5 15:40
+ *  @Description：
+ */
+
+package KnapsackOptimizationTest
+
+import (
+	"Go-Tool/util/KnapsackOptimization"
+	"fmt"
+	"testing"
+)
+
+func TestKnapsackSearchAnswerUtil(t *testing.T) {
+	bagItem := make([]*KnapsackOptimization.BagItem, 0)
+	bagItem = append(bagItem, &KnapsackOptimization.BagItem{
+		Value:  3,
+		Weight: 2,
+	})
+	bagItem = append(bagItem, &KnapsackOptimization.BagItem{
+		Value:  3,
+		Weight: 3,
+	})
+	bagItem = append(bagItem, &KnapsackOptimization.BagItem{
+		Value:  4,
+		Weight: 4,
+	})
+	bagItem = append(bagItem, &KnapsackOptimization.BagItem{
+		Value:  5,
+		Weight: 5,
+	})
+	bagItem = append(bagItem, &KnapsackOptimization.BagItem{
+		Value:  6,
+		Weight: 2,
+	})
+	bagItem = append(bagItem, &KnapsackOptimization.BagItem{
+		Value:  7,
+		Weight: 2,
+	})
+	//通过回溯解背包问题
+	cmd := KnapsackOptimization.NewKnapsackSearchAnswer(bagItem, 12)
+	cmd.DynamicPlanForBestValue()
+	cmd.PrintBestSearchPath()
+	fmt.Println(fmt.Sprintf("最佳价值为：%d", cmd.BestValue()))
+}