Find the number of permutations satisfying a specific adjacency constraint | Step-by-Step Solution
Problem
Count the number of permutations of [n] where Ļ(i+1) ⤠Ļ(i) + 1 for i ā [n-1]
šÆ What You'll Learn
- Understand recursive permutation counting
- Develop skills in combinatorial proof techniques
- Learn multiple proof approaches
Prerequisites: Basic combinatorics, Permutation theory, Inductive reasoning
š” Quick Summary
Hi there! This is a fascinating combinatorics problem involving constrained permutations - you're working with permutations where consecutive elements have a special relationship based on that inequality constraint. What do you think it means intuitively when we say Ļ(i+1) ⤠Ļ(i) + 1, and how might this restriction limit the "shape" or structure of valid permutations? I'd encourage you to think about bijections here - this is one of those beautiful problems where counting the permutations directly is tricky, but there might be a more familiar combinatorial object that behaves in exactly the same way. Consider exploring connections to lattice paths or even tree structures, as constrained permutation problems often have surprising links to these classical counting problems. You've got the mathematical tools to crack this - sometimes the key is recognizing which well-known sequence or structure is hiding behind the constraint!
Step-by-Step Explanation
Hi there! This is a beautiful combinatorics problem that connects permutations with some elegant mathematical structures. Let's break it down together!
What We're Solving:
We need to count permutations Ļ of the set [n] = {1, 2, 3, ..., n} where each element can't "jump up" by more than 1 from its predecessor. Specifically, Ļ(i+1) ⤠Ļ(i) + 1 for all positions i from 1 to n-1.The Approach:
We'll use a clever bijection. We'll show that these special permutations correspond one-to-one with a much simpler object: Dyck paths. This is a classic technique in combinatorics - when counting one thing is hard, find something equivalent that's easier to count!Step-by-Step Solution:
Step 1: Understand what the constraint means The condition Ļ(i+1) ⤠Ļ(i) + 1 means that as we read the permutation from left to right, each new value can be at most 1 larger than the previous value. Think of it as a "gentle ascent" rule.
Step 2: Set up the bijection to Dyck paths We'll convert each valid permutation into a sequence of steps that go either UP (ā) or DOWN (ā).
For a permutation Ļ, create a path by:
- Start at height 0
- For position i = 1 to n: if Ļ(i+1) > Ļ(i), take an UP step; if Ļ(i+1) < Ļ(i), take a DOWN step
- This gives us n-1 steps total
- We can only increase by at most 1 (UP step)
- We can decrease by any amount (DOWN steps)
- Since we use all numbers 1 through n exactly once, the total number of UP steps equals the total number of DOWN steps
Step 5: Count the Dyck paths These permutations correspond to Catalan structures, and the count is the nth Catalan number: $$C_n = \frac{1}{n+1}\binom{2n}{n}$$
The Answer:
The number of permutations of [n] satisfying Ļ(i+1) ⤠Ļ(i) + 1 is the nth Catalan number: $$C_n = \frac{1}{n+1}\binom{2n}{n}$$For small values: Cā = 1, Cā = 2, Cā = 5, Cā = 14, Cā = 42, ...
Memory Tip:
Remember this connection: "Constrained permutations often count the same things as Catalan numbers!" Whenever you see a permutation problem with a "local" constraint (involving adjacent elements), consider whether it might be related to Dyck paths, binary trees, or other Catalan structures. The bijection technique is incredibly powerful in combinatorics!Great work tackling this advanced problem - bijections like this are at the heart of modern combinatorics! š
ā ļø Common Mistakes to Avoid
- Misunderstanding the adjacency constraint
- Failing to consider all permutation possibilities
- Incorrect inductive reasoning
This explanation was generated by AI. While we work hard to be accurate, mistakes can happen! Always double-check important answers with your teacher or textbook.

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š· Problem detected:
Solve: 2x + 5 = 13
Step 1:
Subtract 5 from both sides...
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