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Topic: Greedy Algorithm Problem / Level: advanced
Problem:
Design a Greedy algorithm to allocate limited advertising slots on a popular online platform where each ad has varying viewer engagement potential and expected revenue. Maximize total ad revenue while minimizing viewer dissatisfaction.
More Problems
You are tasked with scheduling repairs for public transportation infrastructure in a city where each project has varying costs, repair durations, and public benefits. Maximize the number of repairs completed while minimizing public disruptions.
Design a Greedy algorithm to allocate limited water resources during a drought where each region has varying population sizes, agricultural needs, and infrastructure capabilities. Maximize total water distribution while minimizing shortages.
You are given a set of scientific experiments where each experiment has varying resource requirements, timelines, and potential breakthroughs. Implement a Greedy algorithm to maximize the number of experiments conducted while minimizing resource wastage.
Design a Greedy algorithm to allocate limited public funds to environmental conservation projects where each project has different ecological impacts, costs, and timelines. Maximize total conservation effectiveness while minimizing resource expenditure.
You are tasked with scheduling the release of high-demand digital products in a tech company where each product has different development times, market demand, and profitability. Maximize total revenue while minimizing production delays.
Design a Greedy algorithm to allocate limited computing resources in a data center where each task has different memory, processing, and execution time requirements. Maximize total task completion while minimizing resource wastage.
You are given a set of marketing campaigns where each campaign has varying costs, reach, and audience engagement potential. Implement a Greedy algorithm to allocate marketing budgets across campaigns to maximize total audience engagement while minimizing expenses.
Design a Greedy algorithm to allocate limited bandwidth across multiple telecommunications networks where each network has varying user demands, data traffic, and potential revenue. Maximize network efficiency while minimizing congestion.
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