huangzj
112 lines
3.6 KiB
Go
112 lines
3.6 KiB
Go
/*
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* @Author : huangzj
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* @Time : 2020/8/5 11:50
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* @Description：
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*/
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package KnapsackOptimization
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import "fmt"
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type KnapsackSearchAnswer struct {
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BagCapacity int //背包的总容量上限
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BagItemList []*BagItem //背包道具列表
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ItemNum int //道具的数量
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bestPath []int //最佳路径(怎么存放价值最高)
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currentBestPath []int //最佳路径(当前解)
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bestValue []int //每个容量最大价值
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currentValue int //当前价值
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currentWeight int //当前重量
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lastBestValue int //目前装载的最优价值
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surplusValue int //剩余道具价值
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}
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func NewKnapsackSearchAnswer(bagItemList []*BagItem, bagCapacity int) *KnapsackSearchAnswer {
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if bagCapacity <= 0 {
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panic("背包总容量不能小于等于0")
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}
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answer := &KnapsackSearchAnswer{
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BagCapacity: bagCapacity,
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BagItemList: bagItemList,
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ItemNum: len(bagItemList),
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bestPath: make([]int, len(bagItemList)+1),
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currentBestPath: make([]int, len(bagItemList)+1),
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bestValue: make([]int, len(bagItemList)+1),
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}
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//初始化剩余道具价值等于所有道具总价值
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for _, r := range bagItemList {
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answer.surplusValue = answer.surplusValue + r.Value
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}
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return answer
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}
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//回溯法计算最佳路径和最大达到价值
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func (cmd *KnapsackSearchAnswer) DynamicPlanForBestValue() {
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cmd.initParam() //初始化第一个数组为空道具
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cmd.BackTrack(1) //从第一个道具开始进行路径搜索
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}
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func (cmd *KnapsackSearchAnswer) BackTrack(step int) {
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//遍历到最后一个道具
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if step > cmd.ItemNum {
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//如果当前总价值大于上一次装载的最佳价值
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if cmd.currentValue > cmd.lastBestValue {
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//最终的最佳路径用当前最佳路径来替换
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for i := 1; i <= cmd.ItemNum; i++ {
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cmd.bestPath[i] = cmd.currentBestPath[i]
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}
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cmd.lastBestValue = cmd.currentValue
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return
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}
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}
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//装入该道具之后，剩余的价值要减去当前道具的价值
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cmd.surplusValue = cmd.surplusValue - cmd.BagItemList[step].Value
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//当前道具的总重量没有超重
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if cmd.currentWeight+cmd.BagItemList[step].Weight <= cmd.BagCapacity {
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cmd.currentBestPath[step] = 1 //当前道具选中了，设置为1
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cmd.currentValue = cmd.currentValue + cmd.BagItemList[step].Value //计算当前价值
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cmd.currentWeight = cmd.currentWeight + cmd.BagItemList[step].Weight //计算当前价值
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cmd.BackTrack(step + 1) //继续遍历下一个道具
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cmd.currentValue = cmd.currentValue - cmd.BagItemList[step].Value //遍历完成要恢复成原来的价值
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cmd.currentWeight = cmd.currentWeight - cmd.BagItemList[step].Weight //遍历完成要恢复成原来的重量
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}
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//这边是剪枝的操作，如果剩余价值加上当前价值会超过上一次的最佳价值，那么就要往右子树遍历，否则不操作.
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if cmd.surplusValue+cmd.currentValue > cmd.lastBestValue {
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cmd.currentBestPath[step] = 0 //当前路径置为0，不选择该位置
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cmd.BackTrack(step + 1)
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}
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cmd.surplusValue = cmd.surplusValue + cmd.BagItemList[step].Value
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}
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//输出最佳路径解
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func (cmd *KnapsackSearchAnswer) PrintBestSearchPath() {
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for index, r := range cmd.bestPath {
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if r == 1 {
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fmt.Print(" ")
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fmt.Println(fmt.Sprintf("道具的价值是:%d,道具的重量是%d", cmd.BagItemList[index].Value, cmd.BagItemList[index].Weight))
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}
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}
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}
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func (cmd *KnapsackSearchAnswer) initParam() {
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itemList := make([]*BagItem, 0)
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itemList = append(itemList, &BagItem{})
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itemList = append(itemList, cmd.BagItemList...)
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cmd.BagItemList = itemList
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}
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func (cmd *KnapsackSearchAnswer) BestValue() int {
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return cmd.lastBestValue
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}
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