algo

Documentation

Overview

Package algo provides implementations of optimisation algorithms.

Index

• func DoCEC2020SOMAT3A(wg *sync.WaitGroup, m *sync.Mutex)
• func DoCEC2020jDE(wg *sync.WaitGroup, m *sync.Mutex)
• func DoRandomSearch(wg *sync.WaitGroup, m *sync.Mutex)
• func DoStochasticHillClimbing(wg *sync.WaitGroup, m *sync.Mutex)
• func DoStochasticHillClimbing100Neigh(wg *sync.WaitGroup, m *sync.Mutex)
• func DojDE(wg *sync.WaitGroup, m *sync.Mutex)
• func GetMeanStats() *stats.MeanStats
• func HillClimb(maxFES, benchMinIters, neighbours int, theD []int, benchFunc string, ...)
• func PlotMeanValsMulti(w *sync.WaitGroup, dimens, iterations int, bench, fPrefix, fExt string, ...)
• func PrepCEC2020ComparisonOfMeans(wg *sync.WaitGroup) (*report.PicList, int)
• func PrepComparisonOfMeans(wg *sync.WaitGroup) (*report.PicList, int)
• func RandomSearchNG(maxFES, benchMinIters int, theD []int, benchFunc string, ch chan []stats.Stats)

Functions

func DoCEC2020SOMAT3A

func DoCEC2020SOMAT3A(wg *sync.WaitGroup, m *sync.Mutex)

DoCEC2020SOMAT3A performs a search using the SOMA T3A method.

func DoCEC2020jDE

func DoCEC2020jDE(wg *sync.WaitGroup, m *sync.Mutex)

func DoRandomSearch

func DoRandomSearch(wg *sync.WaitGroup, m *sync.Mutex)

DoRandomSearch executes a search using the 'Random search' method.

func DoStochasticHillClimbing

func DoStochasticHillClimbing(wg *sync.WaitGroup, m *sync.Mutex)

DoStochasticHillClimbing performs a search using the 'Stochastic Hill Climbing' method.

func DoStochasticHillClimbing100Neigh

func DoStochasticHillClimbing100Neigh(wg *sync.WaitGroup, m *sync.Mutex)

func DojDE

func DojDE(wg *sync.WaitGroup, m *sync.Mutex)

func GetMeanStats

func GetMeanStats() *stats.MeanStats

GetMeanStats returns a pointer of type stats.MeanStats to a sorted package global 'meanStats'.

func HillClimb

func HillClimb(
	maxFES, benchMinIters, neighbours int,
	theD []int,
	benchFunc string,
	ch chan []stats.Stats,
)

HillClimb performs 30 iterations of SHC (30 singleHillClimb func calls internally) to establish a semi-relevant statistical baseline, and reports the results of the computation. nolint: gocognit

func PlotMeanValsMulti

func PlotMeanValsMulti(
	w *sync.WaitGroup,
	dimens, iterations int,
	bench, fPrefix, fExt string,
	algoMeanVals ...stats.AlgoMeanVals,
)

PlotMeanValsMulti creates plots for every member of 'stats.AlgoMeanVals' it is handed and saves them as 'result.Pic's results into a package-global slice.

func PrepCEC2020ComparisonOfMeans

func PrepCEC2020ComparisonOfMeans(wg *sync.WaitGroup) (*report.PicList, int)

PrepCEC2020ComparisonOfMeans prepares for comparison means of CEC2020 algos.

func PrepComparisonOfMeans

func PrepComparisonOfMeans(wg *sync.WaitGroup) (*report.PicList, int)

PrepComparisonOfMeans returns a pointer to a slice of pics (of type report.PicList) and an integer - the count of unique benchmarking functions used.

func RandomSearchNG

func RandomSearchNG(maxFES, benchMinIters int, theD []int, benchFunc string, ch chan []stats.Stats)