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Interactive Algorithm Education

Visualize & Master Algorithms & Data Structures

Explore classic & modern sorting algorithms, efficient searching techniques, and interactive data structure visualizations — all with real-time step-by-step animation, comparisons, swaps, and Big-O metrics.

Greedy Visualizer

Activity Selection

Step 0 / 0
Speed 100ms
Step Progress 0 / 0
Selected 0
Rejected 0
Status Ready
Unconsidered
Considering
Selected
Rejected
Step Explanation

Select an algorithm and press Play to watch the greedy choices unfold.

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Pseudocode 
 
 
 
 
  
 
 
 
  Greedy Algorithms Algorithms 
 
 Greedy Algorithms Algorithm Catalog

 
 3 algorithms in this category. Click any card for detailed analysis.

 
 
 
  
 
 
 Activity Selection 
  Unstable  
  
 Activity Selection picks the maximum number of non-overlapping activities given start and end times. The greedy strategy — always choose the activity that finishes earliest — is provably optimal. 
 
 Ideal Use: For interval scheduling: meeting-room allocation, classroom scheduling, and resource booking with time conflicts. 
  
 
 
Best
 
O(n log n)
 
 
 
Worst
 
O(n log n)
 
 
 
Space
 
O(n)
 
 
  
 Implementation Difficulty 
  ★ ★ ☆ ☆ ☆  2/5 
 Elementary 
  
 
          Graph algorithm — interactive visualization 
 
 
  
   
Inspect & Visualize
  
 
  
 
 
 Fractional Knapsack 
  Unstable  
  
 Fractional Knapsack allows taking fractions of items, so the greedy rule — sort by value/weight ratio and take the best first — achieves the optimal value. Unlike 0/1 Knapsack, greedy is optimal here. 
 
 Ideal Use: For divisible-resource allocation: hauling bulk goods, time-budgeting, and any scenario where resources can be split. 
  
 
 
Best
 
O(n log n)
 
 
 
Worst
 
O(n log n)
 
 
 
Space
 
O(n)
 
 
  
 Implementation Difficulty 
  ★ ★ ☆ ☆ ☆  2/5 
 Elementary 
  
 
          Graph algorithm — interactive visualization 
 
 
  
   
Inspect & Visualize
  
 
  
 
 
 Huffman Coding 
  Unstable  
  
 Huffman Coding builds a prefix-free binary code for a set of symbols, assigning shorter codes to more frequent symbols. Repeatedly merging the two least-frequent nodes into a tree yields the minimum expected code length. 
 
 Ideal Use: Use for lossless data compression: file archivers (DEFLATE/gzip), image formats (JPEG entropy stage), and any stream where symbol frequencies are known or modeled. 
  
 
 
Best
 
O(n log n)
 
 
 
Worst
 
O(n log n)
 
 
 
Space
 
O(n)
 
 
  
 Implementation Difficulty 
  ★ ★ ☆ ☆ ☆  2/5 
 Elementary 
  
 
          Graph algorithm — interactive visualization 
 
 
  
   
Inspect & Visualize
  
 
 
 
 
 
 
 
  Greedy Complexity Matrix 
 

Complexity & Performance Tradeoffs

 

Side-by-side comparison of Big-O time and space complexity characteristics across greedy algorithms.

 
  
 
  
 Algorithm Best Time Average Time Worst Time Space Complexity Stability 
   
   Activity Selection   O(n log n)   O(n log n)   O(n log n)   O(n)    Unstable   
   Fractional Knapsack   O(n log n)   O(n log n)   O(n log n)   O(n)    Unstable   
   Huffman Coding   O(n log n)   O(n log n)   O(n log n)   O(n)    Unstable