The Future of Optical Fibre

An anonymous reader writes "An Australian researcher has come up with a novel way of developing optical fibres. Steven Manos, a researcher at the Optical Fibre Technology Centre in Sydney, Australia has developed a method of using genetic algorithims for discovering optimal designs of optical fibres. An article on his work had this to say "The problem with designing optical fibres is starting with a specific set of criteria and then coming up with a design to fit this. The computer program developed by Manos, which is run on supercomputers, does this by mimicking the process of evolution. The computer program combines two patterns to create a third fibre 'offspring', which Manos described as "similar but a bit different". This process is repeated thousands of times with the 10 designs best suited for the particular application chosen to 'breed' again." Another case of "When in doubt, use brute force"?"

Comments

Brute force? Not exactly

[haluness]

I'd rather not think of the method as brute force. Ok, its not like a design from first principles, but its still way to search the parameter space without having to test all coimbinations of parameters

Re:Brute force? Not exactly

[neilmoore67]

I'd rather not think of the method as brute force.

Well said. Brute force would be enumerating every possible optical fibre and then testing them.

This method is more subtle and converges to a close-to-optimal solution with less computer power having to be applied.

PDFs from Manos

[antic]

There are some interesting PDFs of papers co-written by Steven Manos available including these two:

• Novel fibre Bragg grating design using multiobjective evolutionary algorithms
• Optical Fibre Design with Evolutionary Strategies: Computational implementation and results

I'm not going to pretend that I know exactly what's going on, but the first of those two is worth looking at if you have even a passing interest. The second looks to be a little more towards the "deep end".

Much Better

[irokie]

This is a much better example of the application of Genetic Algorithms than the story that was on slashdot the other day (can't find a link, the one about Formula One racing).

in this case they have a very specific set of criteria.

it didn't however mention in the article how they're testing the designs (did it?)...
and are they actually manufacturing any of the designs that have come from thiss yet?

Only on slashdot...

[Mateito]

.. would breeding be regarded as "brute forcing". :)

GA's are not brute force

[jdrugo]

..as they don't search the state space exhaustively. Going through all possible combinations of parameters would be brute force, but in this case, as the parameters are real-valued, this is even impossible (if ignoring the possibility of quantisation)

Evolutionary Algorithms provide informed search as they perform competition among the individuals (each representing one possible solution) in the population. Their performance is way above exhaustive search techniques (which _are_ brute force) but below classical search techniques. In this case, however, such classical techniques cannot be applied as the problem space is not well-defined.

No, Taco, No

[neoshroom]

Another case of "When in doubt, use brute force"?"

No, Taco, No.

From the 'brute force' entry in Wikipedia:

In computer science, Brute Force, sometimes called the Naive Method, is a term used to refer to the simplest, most intuitive, most spontaneous, and usually most inefficient methods of accomplishing a task.

This is exactly what a genetic algorhthem is not. If you have a million numbers brute force would be to go from the first to the last in order. Using a genetic algorhythem provides a shortcut though Design Space wherein you need to try far fewer combinations in order to come to a successful result.

C'mon Taco, of all people, you should know this!