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Add kotlin codes for the chapter of greedy (#1103)
* feat(kotlin): add kotlin code for dynamic programming. * Update knapsack.kt * feat(kotlin): add kotlin codes for graph. * style(kotlin): reformatted the codes. * feat(kotlin): add kotlin codes for the chapter of greedy. * Update max_product_cutting.kt
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53
codes/kotlin/chapter_greedy/coin_change_greedy.kt
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codes/kotlin/chapter_greedy/coin_change_greedy.kt
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/**
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* File: coin_change_greedy.kt
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* Created Time: 2024-01-25
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* Author: curtishd (1023632660@qq.com)
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*/
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package chapter_greedy
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/* 零钱兑换:贪心 */
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fun coinChangeGreedy(coins: IntArray, amt: Int): Int {
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// 假设 coins 列表有序
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var am = amt
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var i = coins.size - 1
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var count = 0
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// 循环进行贪心选择,直到无剩余金额
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while (am > 0) {
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// 找到小于且最接近剩余金额的硬币
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while (i > 0 && coins[i] > am) {
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i--
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}
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// 选择 coins[i]
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am -= coins[i]
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count++
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}
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// 若未找到可行方案,则返回 -1
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return if (am == 0) count else -1
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}
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/* Driver Code */
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fun main() {
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// 贪心:能够保证找到全局最优解
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var coins = intArrayOf(1, 5, 10, 20, 50, 100)
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var amt = 186
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var res = coinChangeGreedy(coins, amt)
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println("\ncoins = ${coins.contentToString()}, amt = $amt")
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println("凑到 $amt 所需的最少硬币数量为 $res")
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// 贪心:无法保证找到全局最优解
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coins = intArrayOf(1, 20, 50)
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amt = 60
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res = coinChangeGreedy(coins, amt)
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println("\ncoins = ${coins.contentToString()}, amt = $amt")
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println("凑到 $amt 所需的最少硬币数量为 $res")
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println("实际上需要的最少数量为 3 ,即 20 + 20 + 20")
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// 贪心:无法保证找到全局最优解
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coins = intArrayOf(1, 49, 50)
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amt = 98
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res = coinChangeGreedy(coins, amt)
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println("\ncoins = ${coins.contentToString()}, amt = $amt")
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println("凑到 $amt 所需的最少硬币数量为 $res")
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println("实际上需要的最少数量为 2 ,即 49 + 49")
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}
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57
codes/kotlin/chapter_greedy/fractional_knapsack.kt
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codes/kotlin/chapter_greedy/fractional_knapsack.kt
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/**
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* File: fractional_knapsack.kt
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* Created Time: 2024-01-25
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* Author: curtishd (1023632660@qq.com)
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*/
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package chapter_greedy
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import java.util.*
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/* 物品 */
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class Item(
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val w: Int, // 物品
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val v: Int // 物品价值
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)
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/* 分数背包:贪心 */
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fun fractionalKnapsack(
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wgt: IntArray,
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value: IntArray,
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c: Int
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): Double {
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// 创建物品列表,包含两个属性:重量、价值
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var cap = c
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val items = arrayOfNulls<Item>(wgt.size)
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for (i in wgt.indices) {
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items[i] = Item(wgt[i], value[i])
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}
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// 按照单位价值 item.v / item.w 从高到低进行排序
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Arrays.sort(items, Comparator.comparingDouble { item: Item -> -(item.v.toDouble() / item.w) })
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// 循环贪心选择
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var res = 0.0
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for (item in items) {
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if (item!!.w <= cap) {
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// 若剩余容量充足,则将当前物品整个装进背包
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res += item.v.toDouble()
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cap -= item.w
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} else {
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// 若剩余容量不足,则将当前物品的一部分装进背包
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res += item.v.toDouble() / item.w * cap
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// 已无剩余容量,因此跳出循环
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break
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}
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}
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return res
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}
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/* Driver Code */
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fun main() {
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val wgt = intArrayOf(10, 20, 30, 40, 50)
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val values = intArrayOf(50, 120, 150, 210, 240)
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val cap = 50
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// 贪心算法
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val res = fractionalKnapsack(wgt, values, cap)
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println("不超过背包容量的最大物品价值为 $res")
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}
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codes/kotlin/chapter_greedy/max_capacity.kt
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codes/kotlin/chapter_greedy/max_capacity.kt
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/**
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* File: max_capacity.kt
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* Created Time: 2024-01-25
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* Author: curtishd (1023632660@qq.com)
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*/
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package chapter_greedy
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import kotlin.math.max
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import kotlin.math.min
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/* 最大容量:贪心 */
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fun maxCapacity(ht: IntArray): Int {
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// 初始化 i, j,使其分列数组两端
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var i = 0
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var j = ht.size - 1
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// 初始最大容量为 0
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var res = 0
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// 循环贪心选择,直至两板相遇
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while (i < j) {
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// 更新最大容量
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val cap = (min(ht[i].toDouble(), ht[j].toDouble()) * (j - i)).toInt()
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res = max(res.toDouble(), cap.toDouble()).toInt()
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// 向内移动短板
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if (ht[i] < ht[j]) {
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i++
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} else {
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j--
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}
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}
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return res
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}
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/* Driver Code */
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fun main() {
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val ht = intArrayOf(3, 8, 5, 2, 7, 7, 3, 4)
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// 贪心算法
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val res = maxCapacity(ht)
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println("最大容量为 $res")
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}
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codes/kotlin/chapter_greedy/max_product_cutting.kt
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codes/kotlin/chapter_greedy/max_product_cutting.kt
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/**
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* File: max_product_cutting.kt
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* Created Time: 2024-01-25
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* Author: curtishd (1023632660@qq.com)
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*/
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package chapter_greedy
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import kotlin.math.pow
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/* 最大切分乘积:贪心 */
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fun maxProductCutting(n: Int): Int {
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// 当 n <= 3 时,必须切分出一个 1
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if (n <= 3) {
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return 1 * (n - 1)
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}
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// 贪心地切分出 3 ,a 为 3 的个数,b 为余数
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val a = n / 3
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val b = n % 3
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if (b == 1) {
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// 当余数为 1 时,将一对 1 * 3 转化为 2 * 2
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return 3.0.pow((a - 1).toDouble()).toInt() * 2 * 2
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}
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if (b == 2) {
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// 当余数为 2 时,不做处理
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return 3.0.pow(a.toDouble()).toInt() * 2 * 2
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}
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// 当余数为 0 时,不做处理
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return 3.0.pow(a.toDouble()).toInt()
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}
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/* Driver Code */
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fun main() {
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val n = 58
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// 贪心算法
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val res = maxProductCutting(n)
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println("最大切分乘积为 $res")
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}
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