Quintic function added

NiaPy/benchmarks/__init__.py

@@ -17,6 +17,7 @@
 from NiaPy.benchmarks.csendes import Csendes
 from NiaPy.benchmarks.pinter import Pinter
 from NiaPy.benchmarks.qing import Qing
+from NiaPy.benchmarks.quintic import Quintic
 
 
 __all__ = [
@@ -36,5 +37,6 @@
     'ChungReynolds',
     'Csendes',
     'Pinter',
-    'Qing'
+    'Qing',
+    'Quintic'
 ]

NiaPy/benchmarks/quintic.py

@@ -0,0 +1,59 @@
+# encoding=utf8
+# pylint: disable=anomalous-backslash-in-string
+"""Implementation of Quintic function.
+
+Date: 2018
+
+Author: Lucija Brezočnik
+
+License: MIT
+
+Function: Quintic function
+
+Input domain:
+    The function can be defined on any input domain but it is usually
+    evaluated on the hypercube x_i ∈ [-10, 10], for all i = 1, 2,..., D.
+
+Global minimum:
+    f(x*) = 0, at x* = f(-1 or 2)
+
+LaTeX formats:
+    Inline: $f(\mathbf{x}) = \sum_{i=1}^D \left| x_i^5 - 3x_i^4 +
+            4x_i^3 + 2x_i^2 - 10x_i - 4\right|$
+    Equation:  \begin{equation} f(\mathbf{x}) =
+               \sum_{i=1}^D \left| x_i^5 - 3x_i^4 + 4x_i^3 + 2x_i^2 -
+               10x_i - 4\right| \end{equation}
+    Domain: $-10 \leq x_i \leq 10$
+
+Reference paper:
+    Jamil, M., and Yang, X. S. (2013).
+    A literature survey of benchmark functions for global optimisation problems.
+    International Journal of Mathematical Modelling and Numerical Optimisation,
+    4(2), 150-194.
+"""
+
+import math
+
+__all__ = ['Quintic']
+
+
+class Quintic(object):
+
+    def __init__(self, Lower=-10, Upper=10):
+        self.Lower = Lower
+        self.Upper = Upper
+
+    @classmethod
+    def function(cls):
+        def evaluate(D, sol):
+
+            val = 0.0
+
+            for i in range(D):
+                val += abs(math.pow(sol[i], 5) - 3.0 * math.pow(sol[i], 4) + \
+                4.0 * math.pow(sol[i], 3) + 2.0 * math.pow(sol[i], 2) - \
+                10.0 * sol[i] - 4)
+
+            return val
+
+        return evaluate

NiaPy/benchmarks/utility.py

@@ -2,7 +2,7 @@
 
 from . import Rastrigin, Rosenbrock, Griewank, \
     Sphere, Ackley, Schwefel, Schwefel221, \
-    Schwefel222, Whitley, Alpine1, Alpine2, HappyCat, Ridge, ChungReynolds, Csendes, Pinter, Qing
+    Schwefel222, Whitley, Alpine1, Alpine2, HappyCat, Ridge, ChungReynolds, Csendes, Pinter, Qing, Quintic
 
 
 __all__ = ['Utility']
@@ -138,6 +138,13 @@ def get_benchmark(self, benchmark, Lower=None, Upper=None):
                     return Qing(Lower, Upper)
                 else:
                     self.__raiseLowerAndUpperNotDefined()
+            elif benchmark == 'quintic':
+                if Lower is None and Upper is None:
+                    return Quintic()
+                elif Lower is not None and Upper is not None:
+                    return Quintic(Lower, Upper)
+                else:
+                    self.__raiseLowerAndUpperNotDefined()
             else:
                 raise TypeError('Passed benchmark is not defined!')
 

README.md

@@ -44,6 +44,7 @@ The following benchmark functions are included in NiaPy:
 - Happy cat
 - Pintér
 - Qing
+- Quintic
 - Rastrigin
 - Ridge
 - Rosenbrock

examples/run.py

@@ -28,6 +28,6 @@ def evaluate(D, sol):
 algorithms = ['BatAlgorithm', 'DifferentialEvolutionAlgorithm',
               'ArtificialBeeColonyAlgorithm']
 benchmarks = ['sphere', 'ackley', 'rosenbrock', 'griewank', 'rastrigin',
-              'rosenbrock', 'schwefel', 'schwefel221', 'schwefel222', 'whitley', 'alpine1', 'alpine2', 'happyCat', 'ridge', 'chungReynolds', 'csendes', 'pinter', 'qing', MyBenchmark()]
+              'rosenbrock', 'schwefel', 'schwefel221', 'schwefel222', 'whitley', 'alpine1', 'alpine2', 'happyCat', 'ridge', 'chungReynolds', 'csendes', 'pinter', 'qing', 'quintic', MyBenchmark()]
 
 NiaPy.Runner(10, 40, 10000, 10, algorithms, benchmarks).run(export='latex', verbose=True)