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- **Matrix Chain Multiplication (MCM) vs Burst Balloons (BB) β Full Annotated Guide**
- ---
- ## π Problem Setup:
- ### Matrix Chain Multiplication (MCM)
- Given an array `arr` of size `n`, where:
- * Matrix A\_i has dimension `arr[i-1] x arr[i]`
- * Goal: Find the **minimum cost** to multiply matrices A1 \* A2 \* ... \* An
- ### Burst Balloons (BB)
- Given an array `nums` representing balloon values:
- * Bursting balloon at index `k` gives coins: `nums[i-1] * nums[k] * nums[j+1]`
- * Goal: Find the **maximum coins** you can collect by bursting balloons in optimal order
- ---
- ## 1οΈβ£ Inclusive Interval in MCM
- We define `solve(i, j)` to mean multiplying matrices A\_i to A\_j **inclusive**.
- ### Example:
- Let `arr = [10, 20, 30, 40]`:
- * A1: 10x20
- * A2: 20x30
- * A3: 30x40
- To compute A1*A2*A3, we call `solve(1, 3)`
- ### Recurrence:
- ```cpp
- solve(i, j) = min over k in [i, j-1] of:
- solve(i, k) + solve(k+1, j) + arr[i-1] * arr[k] * arr[j];
- ```
- π Visual Representation:
- ```
- arr: [10 20 30 40]
- |----|----|----|
- A1 A2 A3
- i = 1, j = 3 (we're multiplying A1 to A3)
- k = 1:
- βββββββββββ βββββββββββββββββ
- β A1 β x β (A2 x A3) β
- βββββββββββ βββββββββββββββββ
- k = 2:
- βββββββββββββββ βββββββββββ
- β (A1 x A2) β x β A3 β
- βββββββββββββββ βββββββββββ
- ```
- β Why `k` is a Split Point in MCM
- * `k` divides the chain into **two separate multiplication subproblems**
- * You **solve each side recursively**, then multiply the resulting matrices
- * `k` is **not** a matrix, itβs a **cut** between matrices
- ---
- ## 2οΈβ£ Exclusive Interval in Burst Balloons
- We define `solve(i, j)` to mean bursting all balloons in the **exclusive range (i, j)**.
- ### Why Exclusive?
- * Balloons at index `i` and `j` are used as the boundaries to compute coins when `k` is burst.
- * So we must **leave them unburst** until we process a subinterval between them.
- * This allows us to always safely say: `coins = nums[i] * nums[k] * nums[j]` because `i` and `j` are still intact.
- ### Recurrence:
- ```cpp
- solve(i, j) = max over k in (i+1, j-1) of:
- nums[i] * nums[k] * nums[j] + solve(i, k) + solve(k, j);
- ```
- π Visual Representation:
- ```
- nums: [1 3 1 5 8 1]
- ^ ^
- i j
- solve(i, j) => burst between i and j (exclusive)
- k = i+1 to j-1
- ββββββββββββββ ββββββββββββββ
- β solve(i,k) β + β solve(k,j) β + nums[i]*nums[k]*nums[j]
- ββββββββββββββ ββββββββββββββ
- ```
- β Why `k` is the Last to Burst in BB
- * We assume `k` is the last balloon to be popped in range `(i, j)`
- * This means the surroundings (`nums[i]` and `nums[j]`) are still unburst when `k` bursts
- * That's why `k` is **not a divider** but a **last choice**
- ---
- ## π Inclusive vs Exclusive β Summary Table
- | Feature | MCM | Burst Balloons |
- | ----------------------- | ------------------------------------ | ------------------------------------- |
- | Interval Type | Inclusive `[i, j]` | Exclusive `(i, j)` |
- | Meaning of `solve(i,j)` | Multiply matrices A\_i to A\_j | Burst all balloons between i and j |
- | Role of `k` | Divider (split point) | Last balloon to burst |
- | Purpose of Split | Divide chain into two subchains | Defer k until subproblems are solved |
- | Cost Formula | arr\[i-1] \* arr\[k] \* arr\[j] | nums\[i] \* nums\[k] \* nums\[j] |
- | Recursive Merge | Combine results of left Γ right | Add result of left + right + burst(k) |
- | Boundary Behavior | No artificial padding usually needed | Padding with 1s at both ends often |
- ---
- ## π§ Final Takeaways
- ### For MCM:
- * In **MCM**, `solve(i, j)` = cost to multiply full chain A\_i to A\_j
- * Use **inclusive intervals**
- * `k` is a **divider** in `[i, j-1]`
- * Recursively solve left and right, then combine with cost of multiplication
- ### For Burst Balloons:
- * In **BB**, `solve(i, j)` = max coins by bursting balloons **between** i and j
- * Use **exclusive intervals**
- * `k` is the **last to burst** in `(i, j)`
- * Coins are calculated after solving left and right, then bursting `k`
- ---
- Let me know if you'd like this merged content exported as an updated PDF!
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