Examples of Constraint Satisfaction Problems

Understanding Constraint Satisfaction Problems

Constraint Satisfaction Problems (CSPs) are mathematical problems defined as a set of objects whose state must satisfy several constraints and conditions. These problems are common in various fields, including computer science, operations research, and engineering. Below are three diverse examples that illustrate CSPs in different contexts.

Example 1: Scheduling Employees for a Shift

Context

In a retail environment, managers often face the challenge of scheduling employees. The goal is to ensure that shifts are filled while adhering to various constraints such as employee availability, maximum working hours, and legal regulations.

To illustrate, consider a store that requires three shifts to be filled each day: morning, afternoon, and evening. There are five employees available, each with specific availability and maximum working hours.

Example

• Employees: A, B, C, D, E
• Shifts:
  • Morning (M)
  • Afternoon (A)
  • Evening (E)
• Availability:
  • A: M, A
  • B: M, E
  • C: A, E
  • D: M, A
  • E: A
• Constraints:
  • Each shift must have at least 1 employee.
  • No employee can work more than 8 hours in total.

Notes

This example can be varied by changing the number of employees or shifts. Adding constraints, such as limiting consecutive shifts, can also increase complexity.

Example 2: Sudoku Puzzle

Context

Sudoku is a popular puzzle game that exemplifies a constraint satisfaction problem. The objective is to fill a 9x9 grid with digits so that each column, each row, and each of the nine 3x3 grids contain all of the digits from 1 to 9 without repetition.

Example

• Grid: A partially filled Sudoku grid is shown below:

5 3 _ | _ 7 _ | _ _ _ 
6 _ _ | 1 9 5 | _ _ _ 
_ 9 8 | _ _ _ | _ 6 _ 

------+------+------
8 _ _ | _ 6 _ | _ _ 3 
4 _ _ | 8 _ 3 | _ _ 1 
7 _ _ | _ 2 _ | _ _ 6 

------+------+------
_ 6 _ | _ _ _ | 2 8 _ 
_ _ _ | 4 1 9 | _ _ 5 
_ _ _ | _ 8 _ | _ 7 9 

• Constraints:
  • Each row must contain digits 1 to 9 without repetition.
  • Each column must contain digits 1 to 9 without repetition.
  • Each 3x3 grid must contain digits 1 to 9 without repetition.

Notes

Sudoku can be varied by changing the initial numbers and complexity. Different sizes of grids can also be explored, such as 4x4 or 16x16 grids.

Example 3: Traveling Salesman Problem

Context

The Traveling Salesman Problem (TSP) is a classic optimization problem in logistics. The objective is to find the shortest possible route that visits a set of cities and returns to the origin city, meeting specific constraints along the way.

Example

• Cities: A, B, C, D
• Distances (in kilometers):
  • A to B: 10
  • A to C: 15
  • A to D: 20
  • B to C: 35
  • B to D: 25
  • C to D: 30
• Constraints:
  • Each city must be visited exactly once.
  • The route must return to the starting city.

Notes

Variations of TSP can include constraints such as the maximum distance allowed or visiting certain cities in a specific order. The problem can also be extended to consider time windows for visiting cities.

These examples of constraint satisfaction problems illustrate how CSPs can be applied across various domains, highlighting the importance of understanding constraints in problem-solving.