From Slackers to Hackers: How to Maximize Your Code Monkeys’ Profits!
Intuition\n Describe your first thoughts on how to solve this problem. \nImagine you\'re a savvy manager at a tech startup, and you have a bunch of developers (
# Intuition\n<!-- Describe your first thoughts on how to solve this problem. -->\n*Imagine you\'re a savvy manager at a tech startup, and you have a bunch of developers (your workers) with varying levels of skill (difficulty they can handle). You also have a series of tasks, each with a specific difficulty and associated profit. Your goal is to match the developers to the tasks in a way that maximizes your total profit. Think of it like a matchmaking game where you want to assign each worker the most profitable task they can handle without overburdening them.*\n# Approach\n<!-- Describe your approach to solving the problem. -->\n1) Create Worker Objects:\n\n* Create a custom Worker class to encapsulate the difficulty and profit of each task. This makes it easier to manage and sort the tasks later.\n2) Populate Assignments Array:\n\n* Convert the given difficulty and profit arrays into an array of Worker objects. This array will represent all the tasks available.\n3) Sort the Tasks:\n\n* Sort the assignments array by difficulty in ascending order. This allows us to efficiently match each worker with the most profitable task they can handle as we iterate through the sorted workers.\n4) Sort the Workers:\n\n* Sort the worker array in ascending order. This ensures that we process workers from least to most capable, which is crucial for our two-pointer approach.\n5) Match Workers to Tasks:\n\n* Use a two-pointer approach:\n* * Iterate through each worker\'s ability.\n* * For each worker, find the maximum profit task they can handle by moving a pointer through the sorted assignments.\n* * Keep track of the maximum profit found so far for any given difficulty, and use this to accumulate the total profit for all workers.\n# Complexity\n- Time complexity:O(nlogn + mlogm)\n<!-- Add your time complexity here, e.g. $$O(n)$$ -->\n\n- Space complexity:O(n)\n<!-- Add your space complexity here, e.g. $$O(n)$$ -->\n\n# Code\n```\nclass Solution {\n    class Worker{\n        int diff,profit;\n        Worker(int diff,int profit){\n            this.diff=diff;\n            this.profit=profit;\n        }\n    }\n    public int maxProfitAssignment(int[] difficulty, int[] profit, int[] worker) {\n        Worker[] assignments=new Worker[profit.length];\n        for(int i=0;i<profit.length;i++){\n            assignments[i]=new Worker(difficulty[i],profit[i]);\n        }\n        Arrays.sort(assignments,(a,b)->a.diff-b.diff);\n        Arrays.sort(worker);\n        int max=0,ans=0,i=0;\n        for(int j:worker){\n            while(i<assignments.length && assignments[i].diff<=j){\n                max=Math.max(max,assignments[i].profit);\n                i++;\n            }\n            ans+=max;\n        }\n        return ans;\n    }\n}\n```
['Java']