You're offline — cached pages and worlds still work
Drishti Innovations logo
Drishti Innovations

Constraint

Advanced Puzzles: Constraint

Constraint

Constraint

What you'll learn

  • How constraint satisfaction puzzles encode rules as must-be, cannot-be, and conditional links.
  • To formalise clues as logical constraints before searching for solutions.
  • To detect contradiction early and prune impossible branches.
  • To apply constraint thinking to scheduling, seating, and allocation problems in Class 12 reasoning.

Key concepts

Level 1 — Foundations

Verbal: A constraint is any rule the solution must obey. Collect all constraints before placing values.

Constraint categories:

TypeSymbolExample
UnaryX = aRavi in Team A
BinaryX ≠ YRavi not with Priya
ImplicationX → YIf rain, match off
Cardinalitycount(X)=kExactly two doctors
Globalall differentAll cities distinct

Propagation: When Ravi in Team A, remove Ravi from Team B column (all-different). When Team A full, others forced to Team B.

Level 2 — Exam depth

Hard constraints first: Apply most restrictive rules early (exact count, fixed position).

Soft constraints: Preferences ("prefer morning slot") — only after hard rules satisfied in optimisation puzzles.

Constraint graph: Nodes = variables; edges = constraints — helps see which variables are tightly coupled.

Infeasibility signal: Empty domain for any variable → backtrack or re-read clues.

Exam parallel: Sudoku is pure constraint satisfaction — same propagation mindset.

Worked example

Schedule three exams in three slots with constraints

Subjects: Math, Physics, Chemistry. Slots: Mon, Tue, Wed (one each).
(1) Math not Mon. (2) Chemistry before Physics. (3) Physics not Wed.
Step 1 — Order: Chem < Phys in {Mon,Tue,Wed} → Chem Mon, Phys Tue OR Chem Tue, Phys Wed.
Step 2 — Phys not Wed → Chem Mon, Phys Tue, Chem can't be Wed if Phys Tue... Chem Mon, Phys Tue, Math Wed.
Step 3 — Math not Mon ✓ (Math Wed). **Mon=Chem, Tue=Phys, Wed=Math**.

Detect contradiction from constraints

A must be 1 or 2. B must be 1. A ≠ B → A cannot be 1 → A=2. If another clue says A=1, **contradiction** — recheck clue reading.

Common mistakes

MistakeWhy it happensFix
Treating preference as mandatorySoft/hard confusedLabel constraints by type
Missing transitive constraintA≠B, B≠C doesn't mean A≠CDerive all implied constraints
Ignoring cardinalityThree slots, four itemsCount variables vs slots first
Restart without recording eliminationsRepeat same wrong branchKeep elimination log

Quick check

  • Write "Either A in 1 or B in 5" as constraint types.
  • What happens if all domains empty for one variable?
  • Difference between implication and inequality constraint?
  • Stretch: Map seating puzzle clues to constraint table with 5 rows.

Revision tip: Revisit adjacent topics in Advanced Puzzles before mixed practice on Constraint.

Open the Practice tab for graded questions on Constraint.

Exam strategy

Translate English clues into symbols on rough paper (A≠B, A→B) before touching the matrix. Apply cardinality constraints (exactly two, at most one) immediately — they shrink domains fastest. When a branch contradicts, mark the branching clue and try the alternate only once. Constraint puzzles reward patience; rushing placements causes cascade errors.

Practice connections

Constraint propagation is the engine behind Sudoku, grouping, and multi-variable grids — one skill, many skins. Scheduling questions encode constraints as precedence (A before B) — draw arrows before filling calendars. In optimisation, constraints define feasible region; objective picks the best point inside. Programming-minded students may note similarity to if-then rules in spreadsheets — same logic, friendlier notation.

Key Takeaways (TL;DR)

  • What you'll learn
  • Key concepts
  • Worked example
  • Common mistakes

Master this topic with Drishti OS

Get unlimited mock tests, AI-powered mentorship, and complete video courses when you join.

Start Free Practice