<p>This can be calculated quite easily in the context of 8-queen problem. Just start with a particular configuration. Starting from the queen in the left-most column just keep on counting the non-attacking positions (pairs) on the right with each queen. Carry on column by column towards your right until you reach the last queen. As a special case for the last queen the non-attacking pairs will be zero as their are no other queens after that. </p>

CC BY-SA 4.0
2019-12-02T11:23:29.330Z
This describes how to solve the problem, but it doesn't answer the question which is about  formulating this as a fitness function to use in evolutionary computing.
Oliver Mason
CC BY-SA 4.0
2019-12-01T00:57:42.820Z
2019-12-01T00:57:42.820Z
MuneshSingh
<p><a href="https://kushalvyas.github.io/gen_8Q.html" rel="nofollow noreferrer">Here</a> you can find an example of how to apply genetic algorithms to solve the 8-queens problem.</p>
<p>The proposed fitness function is based on the chessboard arrangement, and in particular, it is inversely proportional to the number of clashes amongst attacking positions of queens; thus, a high fitness value implies a low number of clashes.</p>

CC BY-SA 4.0
2018-11-24T13:24:35.257Z
2021-01-30T02:34:28.230Z
2021-01-30T02:34:28.230Z
PieCot
<p>In evolutionary computation and, in particular, in the context of genetic algorithms, there is the concept of a <a href="https://en.wikipedia.org/wiki/Fitness_function" rel="nofollow noreferrer"><em>fitness function</em></a>. The better a state, the greater the value of the fitness function for that state.</p>
<p>What would be a good fitness function for the <a href="https://en.wikipedia.org/wiki/Eight_queens_puzzle" rel="nofollow noreferrer">8-queens problem</a>?</p>

<genetic-algorithms><fitness-functions><evolutionary-computation><fitness-design><8-queens-problem>
How to design a fitness function for the 8-queens problem?
Huma Qaseem
# How to design a fitness function for the 8-queens problem?

(Asked by: username_0 on 2018-11-22)

In evolutionary computation and, in particular, in the context of genetic algorithms, there is the concept of a [*fitness function*](https://en.wikipedia.org/wiki/Fitness_function). The better a state, the greater the value of the fitness function for that state.

What would be a good fitness function for the [8-queens problem](https://en.wikipedia.org/wiki/Eight_queens_puzzle)?

**Tags:** genetic-algorithms, fitness-functions, evolutionary-computation, fitness-design, 8-queens-problem


---

## 2 answers

### Answer by username_3 on 2018-11-24. Score: 2 | Accepted answer

[Here](https://kushalvyas.github.io/gen_8Q.html) you can find an example of how to apply genetic algorithms to solve the 8-queens problem.

The proposed fitness function is based on the chessboard arrangement, and in particular, it is inversely proportional to the number of clashes amongst attacking positions of queens; thus, a high fitness value implies a low number of clashes.


---

### Answer by username_1 on 2019-12-01. Score: 0

This can be calculated quite easily in the context of 8-queen problem. Just start with a particular configuration. Starting from the queen in the left-most column just keep on counting the non-attacking positions (pairs) on the right with each queen. Carry on column by column towards your right until you reach the last queen. As a special case for the last queen the non-attacking pairs will be zero as their are no other queens after that.

> **Comments:**
> **username_2**: This describes how to solve the problem, but it doesn't answer the question which is about  formulating this as a fitness function to use in evolutionary computing.  

---

