Merge branch 'dev'

moead_framework/problem/combinatorial/mubqp.py

@@ -0,0 +1,61 @@
+import numpy as np
+from moead_framework.problem.problem import Problem
+from moead_framework.solution.one_dimension_solution import OneDimensionSolution
+
+
+class Mubqp(Problem):
+
+    def __init__(self, instance_file):
+        file = open(instance_file, 'r')
+        file_content = list(map(str.strip, file.readlines()))
+        file.close()
+
+        file_content = file_content[6:]
+
+        definition = file_content[0].split(" ")
+        self.rho = float(definition[2])
+        self.m = int(definition[3])
+        self.n = int(definition[4])
+        self.d = float(definition[5])
+        file_content = file_content[2:]
+
+        super().__init__(objective_number=self.m)
+
+        self.qs = np.zeros((self.m, self.n, self.n))
+        self.load_qs(file_content)
+
+    def f(self, function_id, solution):
+        fit = 0
+
+        for i in range(self.n):
+            if solution[i] == 1:
+                for j in range(i+1):
+                    if solution[j] == 1:
+                        fit += self.qs[function_id][i][j]
+
+        return fit
+
+    def generate_random_solution(self, evaluate=True):
+        return self.generate_solution(array=np.random.randint(0, 2, self.n).tolist()[:], evaluate=evaluate)
+
+    def generate_solution(self, array, evaluate=True):
+        x = OneDimensionSolution(np.array(array, dtype=int))
+
+        for j in range(self.function_numbers):
+            if evaluate:
+                x.F.append(self.f(j, x.solution))
+            else:
+                x.F.append(None)
+
+        return x
+
+    def load_qs(self, array):
+        line = 0
+        for i in range(self.n):
+            for j in range(self.n):
+                s = array[line].split("  ")
+                line += 1
+                for n in range(self.m):
+                    self.qs[n][i][j] = int(s[n])
+                pass
+