Answer :
Answer:The Traveling Salesperson Problem (TSP) is a classic problem in computer science and optimization theory where the goal is to find the shortest possible route that visits each city exactly once and returns to the starting point. Let's break down the requirements step by step:
### 1. Set of States and Operators, and State Space Construction
**Set of States:**
In the TSP, a state can be defined as a permutation of cities that the salesperson visits. Each state represents a particular sequence in which cities are visited.
**Operators:**
The operators define how the salesperson can move from one state (permutation) to another. In TSP, the operators would involve swapping two cities in the sequence (permutation) of cities.
**State Space Construction:**
- **Initial State:** This is the starting point of the salesperson's journey, typically City 1.
- **Goal State:** A goal state is a state where all cities have been visited exactly once and the salesperson returns to the starting city (City 1), having completed the tour.
- **State Transitions:** Transitions between states occur by swapping the positions of two cities in the current permutation. For example, if the current state (permutation) is \( [1, 2, 3, 4] \), possible state transitions could be \( [1, 2, 4, 3] \) by swapping positions of cities 3 and 4.
Constructing the entire state space involves generating all possible permutations of cities except for the starting city, as the salesperson must return to the starting city at the end.
### 2. Goal Test Function
The goal test function checks whether a given state is a goal state:
- It verifies if all cities have been visited exactly once (i.e., the permutation contains all cities exactly once except for the starting city).
- It checks if the salesperson returns to the starting city after visiting all other cities.
### 3. Path Cost
The path cost in TSP is the total distance (or cost) of the route taken by the salesperson. This cost is calculated based on the distances between consecutive cities visited in the permutation.
To summarize:
- **Set of States:** Permutations of cities (excluding the starting city).
- **Operators:** Swapping two cities in the permutation.
- **State Space:** All possible permutations of cities excluding the starting city.
- **Goal Test Function:** Checks if all cities have been visited exactly once and the salesperson returns to the starting city.
- **Path Cost:** Total distance (or cost) of the route taken by the salesperson.
Implementing these components would allow you to construct and solve the Traveling Salesperson Problem efficiently.
Explanation:
