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Topic: Greedy Algorithm Problem / Level: advanced
Problem:
Design a Greedy algorithm to allocate vaccine doses during a pandemic where each region has different population sizes, infection rates, and healthcare infrastructure. Maximize vaccination coverage while minimizing transportation delays.
More Problems
You are given a set of tasks in a parallel processing system where each task has different execution times and memory requirements. Implement a Greedy algorithm to maximize total system throughput while minimizing memory usage.
Design a Greedy algorithm to allocate computing resources in a data center where each server has varying power consumption, processing capacity, and user demands. Maximize total server utilization while minimizing power costs.
You are tasked with scheduling a series of live events where each event has varying durations, audience engagement, and ticket prices. Maximize total ticket sales while minimizing event overlaps.
Design a Greedy algorithm to allocate limited bandwidth across multiple video streaming services where each service has varying viewer engagement and data usage. Maximize viewer satisfaction while minimizing bandwidth usage.
You are given a set of jobs in a distributed computing environment where each job has different CPU, memory, and network requirements. Implement a Greedy algorithm to maximize total job completion while minimizing network congestion.
Design a Greedy algorithm to allocate a limited number of hospital beds where each hospital has different patient loads and treatment requirements. Maximize patient care while minimizing bed shortages.
You are tasked with scheduling energy production in a power grid where each energy source has different production rates, costs, and environmental impacts. Maximize total energy output while minimizing environmental damage.
Design a Greedy algorithm to allocate research grants to scientific projects where each project has different potential for breakthroughs and varying funding needs. Maximize total research output while minimizing the total budget used.
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