private static ISearchStrategy LS1(TerminateStrategy ts) => new LS(
initalise: new RandomInitalise(),
neighbourhood: new TwoOpt(),
step: new LowestCost(),
terminate: ts,
name: "Local Search - Random initialisations"
);
private static ISearchStrategy RND(TerminateStrategy ts) => new LS(
initalise: new RandomInitalise(),
neighbourhood: new NonNeighbourhood(),
step: new LowestCost(),
terminate: ts,
name: "Random Search"
);
public LocalSearch(IInitalise initalise, INeighbourhood neighbourhood, IStepFunction step, TerminateStrategy terminate, string name = "Local Search")
{
this.initalisationStrategy = initalise;
this.neighbourhood = neighbourhood;
this.step = step;
this.terminateStrategy = terminate;
this.name = name;
}
/// <summary>
/// Generates a list of available searches with a given <see cref="TerminateStrategy"/>
/// </summary>
/// <param name="ts">The <see cref="TerminateStrategy"/> that is to be used (may be ignored by some searches eg Greedy Search)</param>
/// <returns>A list of searches</returns>
internal static List <ISearchStrategy> GenerateSearches(TerminateStrategy ts)
{
return(new List <ISearchStrategy>()
{
new ExhaustiveSearch(),
RND(ts),
LS1(ts),
LS2(),
GN1(ts, 100, 20),
});
}
private static ISearchStrategy GN1(TerminateStrategy ts, uint populationSize, uint k, float elitism = 0.2f, float mutationRate = 0.04f) => new Evolution(
initalise: new RandomInitalise(),
selectionStrategy: new TournamentSelection(k),
crossoverStratergy: new OrderedCrossover(),
swap: new TwoOpt(),
stepFunction: new LowestCost(),
terminate: ts,
populationSize: populationSize,
eliteism: elitism,
mutationRate: mutationRate,
name: "Evolutionary Search - Tournament"
);
public Evolution(IInitalise initalise, ISelectionStrategy selectionStrategy, ICrossover crossoverStratergy, ISwap swap, TerminateStrategy terminate, IStepFunction stepFunction, uint populationSize, float eliteism, float mutationRate, string name = "Evolution Search")
{
this.InitalisationStrategy = initalise;
this.selectionStrategy = selectionStrategy;
this.crossoverStratergy = crossoverStratergy;
this.step = stepFunction;
this.swap = swap;
this.terminateStrategy = terminate;
this.name = name;
this.eliteism = eliteism;
this.mutationRate = mutationRate;
population = new Route[populationSize];
}
