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Topic: Greedy Algorithm Problem / Level: advanced
Problem:
Design a Greedy algorithm to allocate advertising space on popular websites where each ad has varying engagement levels and costs. Maximize total revenue while minimizing ad conflicts and user dissatisfaction.
More Problems
You are given a set of cities with varying pollution levels and road conditions. Implement a Greedy algorithm to allocate limited resources to build new roads that minimize pollution and maximize accessibility.
Design a Greedy algorithm to allocate a fleet of autonomous taxis in a city where each taxi has different capacities and routes. Maximize total passenger satisfaction while minimizing fuel costs and traffic congestion.
You are tasked with scheduling maintenance for a fleet of commercial airplanes where each airplane has different flight schedules, maintenance costs, and passenger capacity. Maximize fleet uptime while minimizing maintenance delays.
Design a Greedy algorithm to allocate internet bandwidth across a large data center where each server has different processing requirements and bandwidth demands. Maximize total system performance while minimizing bandwidth congestion.
You are given a set of power plants with varying energy outputs and environmental impacts. Implement a Greedy algorithm to allocate energy production in a way that maximizes total output while minimizing environmental damage.
Design a Greedy algorithm to allocate advertising slots during a live sports broadcast where each ad has different viewer engagement potential and revenue. Maximize total revenue while minimizing viewer disruption.
You are tasked with scheduling the release of vaccines in a country where each region has different population sizes, infection rates, and healthcare infrastructure. Maximize total vaccination coverage while minimizing distribution delays.
Design a Greedy algorithm to allocate limited transportation vehicles during a large-scale emergency where each vehicle has different capacities and travel routes. Maximize the number of people evacuated while minimizing travel time and fuel costs.
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