NiaOrg /
NiaPy
| @@ 21-45 (lines=25) @@ | ||
| 18 | ||
| 19 | def generateSolution(self): |
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| 20 | self.Solution = [self.LB + (self.UB - self.LB) * rnd.random() |
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| 21 | for _i in range(self.D)] |
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| 22 | ||
| 23 | def evaluate(self): |
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| 24 | self.Fitness = SolutionDE.FuncEval(self.D, self.Solution) |
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| 25 | ||
| 26 | def repair(self): |
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| 27 | for i in range(self.D): |
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| 28 | if self.Solution[i] > self.UB: |
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| 29 | self.Solution[i] = self.UB |
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| 30 | if self.Solution[i] < self.LB: |
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| 31 | self.Solution[i] = self.LB |
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| 32 | ||
| 33 | def __eq__(self, other): |
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| 34 | return self.Solution == other.Solution and self.Fitness == other.Fitness |
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| 35 | ||
| 36 | ||
| 37 | class DifferentialEvolutionAlgorithm(object): |
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| 38 | r"""Implementation of Differential evolution algorithm. |
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| 39 | ||
| 40 | **Algorithm:** Differential evolution algorithm |
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| 41 | ||
| 42 | **Date:** 2018 |
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| 43 | ||
| 44 | **Author:** Uros Mlakar |
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| 45 | ||
| 46 | **License:** MIT |
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| 47 | ||
| 48 | **Reference paper:** |
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| @@ 25-51 (lines=27) @@ | ||
| 22 | def repair(self): |
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| 23 | for i in range(self.D): |
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| 24 | if self.Solution[i] > self.UB: |
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| 25 | self.Solution[i] = self.UB |
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| 26 | ||
| 27 | if self.Solution[i] < self.LB: |
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| 28 | self.Solution[i] = self.LB |
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| 29 | ||
| 30 | def evaluate(self): |
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| 31 | self.Fitness = SolutionABC.FuncEval(self.D, self.Solution) |
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| 32 | ||
| 33 | def toString(self): |
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| 34 | pass |
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| 35 | ||
| 36 | ||
| 37 | class ArtificialBeeColonyAlgorithm(object): |
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| 38 | r"""Implementation of Artificial Bee Colony algorithm. |
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| 39 | ||
| 40 | **Algorithm:** Artificial Bee Colony algorithm |
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| 41 | ||
| 42 | **Date:** 2018 |
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| 43 | ||
| 44 | **Author:** Uros Mlakar |
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| 45 | ||
| 46 | **License:** MIT |
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| 47 | ||
| 48 | **Reference paper:** |
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| 49 | Karaboga, D., and Bahriye B. "A powerful and efficient algorithm for |
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| 50 | numerical function optimization: artificial bee colony (ABC) algorithm." |
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| 51 | Journal of global optimization 39.3 (2007): 459-471. |
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| 52 | ||
| 53 | """ |
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| 54 | ||
| @@ 7-37 (lines=31) @@ | ||
| 4 | ||
| 5 | __all__ = ['SelfAdaptiveDifferentialEvolutionAlgorithm'] |
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| 6 | ||
| 7 | ||
| 8 | class SolutionjDE(object): |
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| 9 | ||
| 10 | def __init__(self, D, LB, UB, F, CR): |
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| 11 | self.D = D |
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| 12 | self.LB = LB |
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| 13 | self.UB = UB |
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| 14 | self.F = F |
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| 15 | self.CR = CR |
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| 16 | self.Solution = [] |
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| 17 | self.Fitness = float('inf') |
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| 18 | self.generateSolution() |
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| 19 | ||
| 20 | def generateSolution(self): |
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| 21 | """Generate solution.""" |
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| 22 | ||
| 23 | self.Solution = [self.LB + (self.UB - self.LB) * rnd.random() |
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| 24 | for _i in range(self.D)] |
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| 25 | ||
| 26 | def evaluate(self): |
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| 27 | """Evaluate solution.""" |
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| 28 | ||
| 29 | self.Fitness = SolutionjDE.FuncEval(self.D, self.Solution) |
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| 30 | ||
| 31 | def repair(self): |
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| 32 | for i in range(self.D): |
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| 33 | if self.Solution[i] > self.UB: |
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| 34 | self.Solution[i] = self.UB |
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| 35 | if self.Solution[i] < self.LB: |
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| 36 | self.Solution[i] = self.LB |
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| 37 | ||
| 38 | def __eq__(self, other): |
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| 39 | return self.Solution == other.Solution and self.Fitness == other.Fitness |
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| 40 | ||
| @@ 8-37 (lines=30) @@ | ||
| 5 | __all__ = ['GeneticAlgorithm'] |
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| 6 | ||
| 7 | ||
| 8 | class Chromosome(object): |
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| 9 | def __init__(self, D, LB, UB): |
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| 10 | self.D = D |
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| 11 | self.LB = LB |
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| 12 | self.UB = UB |
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| 13 | ||
| 14 | self.Solution = [] |
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| 15 | self.Fitness = float('inf') |
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| 16 | self.generateSolution() |
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| 17 | ||
| 18 | def generateSolution(self): |
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| 19 | self.Solution = [self.LB + (self.UB - self.LB) * rnd.random() |
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| 20 | for _i in range(self.D)] |
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| 21 | ||
| 22 | def evaluate(self): |
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| 23 | self.Fitness = Chromosome.FuncEval(self.D, self.Solution) |
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| 24 | ||
| 25 | def repair(self): |
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| 26 | for i in range(self.D): |
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| 27 | if self.Solution[i] > self.UB: |
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| 28 | self.Solution[i] = self.UB |
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| 29 | if self.Solution[i] < self.LB: |
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| 30 | self.Solution[i] = self.LB |
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| 31 | ||
| 32 | def __eq__(self, other): |
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| 33 | return self.Solution == other.Solution and self.Fitness == other.Fitness |
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| 34 | ||
| 35 | def toString(self): |
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| 36 | print([i for i in self.Solution]) |
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| 37 | ||
| 38 | ||
| 39 | class GeneticAlgorithm(object): |
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| 40 | r"""Implementation of Genetic algorithm. |
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