EdocGram
Home
(current)
Topics
EdocAI
Code Editor
HTML
Javascript
PHP
Python
Python AI Code Editor
More
Contact
About
Privacy Policy
Terms and Conditions
Log In
Topic: Greedy Algorithm Problem / Level: advanced
Problem:
You are given a set of cities and a network of roads with varying traffic conditions and toll prices. Design a Greedy algorithm to minimize the total travel cost between two cities, considering both time and cost.
More Problems
Implement a Greedy algorithm to maximize the profit in an investment portfolio where each investment has a different ROI and risk factor. The goal is to maximize profit while minimizing risk.
Design a Greedy algorithm to allocate tasks among workers in a construction project, where each task has different resource requirements and deadlines. The goal is to maximize the completion rate while minimizing resource overuse.
You are tasked with developing a Greedy algorithm to schedule flights in an airport with limited runways, where each flight has a different priority level, duration, and cost. Maximize the number of flights scheduled without delays.
Given a set of jobs with varying deadlines and profits, design a Greedy algorithm to maximize the total profit while minimizing job conflicts in a dynamic environment with changing job availabilities.
You are given a set of cities, each with a different resource production capacity. Design a Greedy algorithm to maximize the total resource distribution among cities while minimizing transportation costs.
Design a Greedy algorithm to minimize the total energy consumption in a data center, where each server has a different power efficiency and task allocation. The goal is to minimize energy use while meeting all task deadlines.
You are tasked with allocating a limited number of vehicles to deliver goods between warehouses, where each vehicle has a different capacity and cost. Design a Greedy algorithm to maximize delivery efficiency while minimizing costs.
Implement a Greedy algorithm to optimize the deployment of a limited number of wireless access points in a city, where each access point has a different range and cost. Maximize coverage while minimizing cost.
Python
Language
Editor
Run & Output
Save
AI Code Generate
AI Test Case
Run the code to see the output here...