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Advanced Greedy

Complex greedy algorithm problems and advanced applications.

Interval scheduling​

  • Problem: Schedule maximum number of non-overlapping intervals
  • Greedy Choice: Select interval with earliest finish time
  • Variations: Weighted intervals, multiple resources
  • Applications: Resource allocation, task scheduling

Set cover​

  • Problem: Find minimum number of sets that cover all elements
  • Greedy Choice: Select set covering most uncovered elements
  • Approximation: Greedy algorithm provides good approximation
  • Applications: Facility location, network design

Job scheduling​

  • Problem: Schedule jobs to minimize completion time or maximize profit
  • Greedy Choice: Sort jobs by specific criteria
  • Variations: Precedence constraints, multiple machines
  • Applications: CPU scheduling, project management

Resource allocation​

  • Problem: Allocate limited resources optimally
  • Greedy Choice: Allocate to highest priority/benefit
  • Constraints: Resource limits, fairness requirements
  • Applications: Budget allocation, network bandwidth

Optimization problems​

  • Problem: Find optimal solution under constraints
  • Greedy Choice: Make locally optimal decision
  • Trade-offs: Balance multiple objectives
  • Applications: Portfolio optimization, route planning