Problem or limitation
Greedy is used when:
-Problem has optimal substructure
-Problem has greedy choice property
-Local best choice leads to global best solution
Proposed solution
Greedy algorithms are used to solve optimization problems where:
- We want the maximum or minimum result
- We make decisions step by step
- At each step, we choose the best possible option right now (locally optimal choice)
Alternatives considered
No response
Use case
🧩Problem:
You are given multiple activities with start and end times.
You must select the maximum number of non-overlapping activities.
🎯 Goal:
Maximize number of activities without conflict.
💡 Greedy Idea (Proposed Solution):
Always pick the activity that finishes earliest
This leaves maximum time for remaining activities
Sort activities by end time
Select next activity only if it starts after last selected activity ends
Additional context
No response
Problem or limitation
Greedy is used when:
-Problem has optimal substructure
-Problem has greedy choice property
-Local best choice leads to global best solution
Proposed solution
Greedy algorithms are used to solve optimization problems where:
Alternatives considered
No response
Use case
🧩Problem:
You are given multiple activities with start and end times.
You must select the maximum number of non-overlapping activities.
🎯 Goal:
Maximize number of activities without conflict.
💡 Greedy Idea (Proposed Solution):
Always pick the activity that finishes earliest
This leaves maximum time for remaining activities
Sort activities by end time
Select next activity only if it starts after last selected activity ends
Additional context
No response