NiaOrg /
NiaPy
| @@ 59-74 (lines=16) @@ | ||
| 56 | """ |
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| 57 | return r"""Yang, Xin-She. "Harmony search as a metaheuristic algorithm." Music-inspired harmony search algorithm. Springer, Berlin, Heidelberg, 2009. 1-14.""" |
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| 58 | ||
| 59 | @staticmethod |
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| 60 | def typeParameters(): |
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| 61 | r"""Get dictionary with functions for checking values of parameters. |
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| 62 | ||
| 63 | Returns: |
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| 64 | Dict[str, Callable]: |
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| 65 | * HMS (Callable[[int], bool]) |
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| 66 | * r_accept (Callable[[float], bool]) |
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| 67 | * r_pa (Callable[[float], bool]) |
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| 68 | * b_range (Callable[[float], bool]) |
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| 69 | """ |
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| 70 | return { |
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| 71 | "HMS": lambda x: isinstance(x, int) and x > 0, |
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| 72 | "r_accept": lambda x: isinstance(x, float) and 0 < x < 1, |
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| 73 | "r_pa": lambda x: isinstance(x, float) and 0 < x < 1, |
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| 74 | "b_range": lambda x: isinstance(x, (int, float)) and x > 0 |
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| 75 | } |
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| 76 | ||
| 77 | def setParameters(self, HMS=30, r_accept=0.7, r_pa=0.35, b_range=1.42, **ukwargs): |
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| @@ 157-163 (lines=7) @@ | ||
| 154 | """ |
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| 155 | return r"""Tan, Ying. "Firework Algorithm: A Novel Swarm Intelligence Optimization Method." (2015).""" |
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| 156 | ||
| 157 | @staticmethod |
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| 158 | def typeParameters(): return { |
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| 159 | 'N': lambda x: isinstance(x, int) and x > 0, |
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| 160 | 'm': lambda x: isinstance(x, int) and x > 0, |
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| 161 | 'a': lambda x: isinstance(x, (int, float)) and x > 0, |
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| 162 | 'b': lambda x: isinstance(x, (int, float)) and x > 0, |
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| 163 | 'epsilon': lambda x: isinstance(x, float) and 0 < x < 1 |
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| 164 | } |
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| 165 | ||
| 166 | def setParameters(self, N=40, m=40, a=1, b=2, A=40, epsilon=1e-31, **ukwargs): |
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| @@ 67-84 (lines=18) @@ | ||
| 64 | """ |
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| 65 | Name = ['EvolutionStrategy1p1', 'EvolutionStrategy(1+1)', 'ES(1+1)'] |
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| 66 | ||
| 67 | @staticmethod |
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| 68 | def typeParameters(): |
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| 69 | r"""Get dictionary with functions for checking values of parameters. |
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| 70 | ||
| 71 | Returns: |
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| 72 | Dict[str, Callable]: |
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| 73 | * mu (Callable[[int], bool]) |
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| 74 | * k (Callable[[int], bool]) |
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| 75 | * c_a (Callable[[Union[float, int]], bool]) |
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| 76 | * c_r (Callable[[Union[float, int]], bool]) |
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| 77 | * epsilon (Callable[[float], bool]) |
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| 78 | """ |
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| 79 | return { |
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| 80 | 'mu': lambda x: isinstance(x, int) and x > 0, |
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| 81 | 'k': lambda x: isinstance(x, int) and x > 0, |
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| 82 | 'c_a': lambda x: isinstance(x, (float, int)) and x > 1, |
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| 83 | 'c_r': lambda x: isinstance(x, (float, int)) and 0 < x < 1, |
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| 84 | 'epsilon': lambda x: isinstance(x, float) and 0 < x < 1 |
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| 85 | } |
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| 86 | ||
| 87 | def setParameters(self, mu=1, k=10, c_a=1.1, c_r=0.5, epsilon=1e-20, **ukwargs): |
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