46 lines
2.2 KiB
Markdown
46 lines
2.2 KiB
Markdown
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## Ideas
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- Improve tournament selection testing
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- Refactor models testings
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- Add more context to errors (at least the method/struct name) (https://dave.cheney.net/2016/04/27/dont-just-check-errors-handle-them-gracefully)
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- Add more example usage
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- Implement operators described in http://www.ppgia.pucpr.br/~alceu/mestrado/aula3/IJBB-41.pdf
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- Implement Particle Swarm Optimization
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- http://deap.readthedocs.io/en/master/
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- http://pyevolve.sourceforge.net/intro.html#ga-features
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- http://www.dmi.unict.it/mpavone/nc-cs/materiale/moscato89.pdf
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- Serialize with http://labix.org/gobson, maybe
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## Code style
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### Guidelines
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- Keep names short
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- Aim for 100 characters per line
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### Variable declaration
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```go
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// Good
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x := 42
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// Bad
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var x = 42
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```
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## Naming convention
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Please inspire yourself from the existing algorithms before implementing, the naming conventions are easy to grasp.
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## Parallelism and random number generation caveat
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Genetic algorithms are notorious for being [embarrassingly parallel](http://www.wikiwand.com/en/Embarrassingly_parallel). Indeed, most calculations can be run in parallel because they only affect part of the GA. Luckily Go provides good support for parallelism. As some gophers may have encountered, the `math/rand` module can be problematic because there is a global lock attached to the random number generator. The problem is described in this [StackOverflow post](http://stackoverflow.com/questions/14298523/why-does-adding-concurrency-slow-down-this-golang-code). This can be circumvented by providing each population with it's own random number generator.
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Talking about parallelism, there is a reason why the populations are run in parallel and not the individuals. First of all for parallelism at an individual level each individual would have to be assigned a new random number generator, which isn't very efficient. Second of all, even though Golang has an efficient concurrency model, spawning routines nonetheless has an overhead. It's simply not worth using a routine for each individual because operations at an individual level are often not time consuming enough.
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## Performance
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1. `go test -bench . -cpuprofile=cpu.prof`
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2. `go tool pprof -pdf gago.test cpu.prof > profile.pdf`
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