Study Planner – Dynamic Programming Optimizer

A web-based study planner that uses Dynamic Programming (0/1 Knapsack) to optimize a student’s study schedule for maximum exam marks under limited study hours.

---

🚀 Demo

Link: https://dynamic-program.vercel.app/

Features:

• Add topics with time required and expected marks
• Set study constraints (days & hours/day)
• Click Optimize Study Plan to get:
  • Maximum achievable marks
  • Topics to focus on
  • Hours used
• DP Table Visualization showing step-by-step computation

---

💡 Problem Statement

Students often struggle to decide what topics to focus on when time is limited.
This project models the problem as a 0/1 Knapsack problem:

• Capacity: Total available study hours
• Items: Syllabus topics
• Weight: Time required per topic
• Value: Expected marks per topic

The goal is to maximize marks without exceeding available hours.

---

🛠 Tech Stack

• Frontend: React + Vite
• Styling: Tailwind CSS
• Logic: JavaScript (Dynamic Programming)
• No database required (state is in-memory)

---

⚙️ Features

1. Topic Input
   • Name, Time required (hours), Expected Marks
2. Constraints Input
   • Days before exam, Hours per day
3. Optimization
   • Computes maximum marks using 0/1 Knapsack DP
   • Shows selected topics for focus
4. DP Table Visualization
   • Step-by-step DP array evolution after each topic

---

🧩 How It Works (DP Logic)

1. Create a 1D DP array:

dp[t] = maximum marks achievable using t hours
Iterate through topics:

for each topic:
    for t = totalHours down to topic.time:
        dp[t] = max(dp[t], dp[t-topic.time] + topic.marks)


Track which topics are selected (backtracking using choice array)

Display results and DP table in UI