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Topic: Greedy Algorithm Problem / Level: advanced
Problem:
Design a Greedy algorithm to allocate limited advertising slots on popular digital platforms where each ad has varying viewer engagement and potential revenue. Maximize total revenue while minimizing user dissatisfaction.
More Problems
You are tasked with scheduling the release of high-demand consumer products in a global retail company where each product has different development times, market potential, and revenue margins. Maximize total sales while minimizing production delays.
Design a Greedy algorithm to allocate limited bandwidth across mobile networks in a densely populated city where each network has varying user demands and data traffic. Maximize network performance while minimizing bandwidth congestion.
You are given a set of tasks in a cloud computing environment where each task has different memory, CPU, and execution time requirements. Implement a Greedy algorithm to maximize total task completion while minimizing server usage.
Design a Greedy algorithm to allocate limited water resources in a drought-affected region where each area has varying population sizes, water needs, and infrastructure. Maximize total water distribution while minimizing shortages.
You are tasked with scheduling the deployment of rescue teams during a natural disaster where each region has varying levels of need and logistical challenges. Maximize the number of people rescued while minimizing resource wastage.
Design a Greedy algorithm to allocate limited research grants to scientific projects where each project has varying risks, potential breakthroughs, and funding requirements. Maximize total research output while minimizing financial risk.
You are given a set of marketing campaigns where each campaign has different costs, potential reach, and audience engagement levels. 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 industries where each industry has varying data traffic and economic impact. Maximize total economic output while minimizing bandwidth congestion.
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