28686583443

Committed 03 Jul 2026 10:47PM UTC coverage: 79.757% (-7.4%) from 87.112%

Build # 28686583443

Build Type

Pull #13

github

Committed by

web-flow

Commit Message

Merge 9d44a36d2 into f08badaa8

Pull Request Pull Request #13: Feat/multi objective

Coverage Stats

294 of 760 new or added lines in 13 files covered. (38.68%)

79 existing lines in 5 files now uncovered.

3944 of 4945 relevant lines covered (79.76%)

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98.61

/src/smt_optim/benchmarks/multiobj/constrained.py

import numpy as np

from smt_optim.benchmarks.base import BenchmarkProblem


class BNH(BenchmarkProblem):
    def __init__(self):
        super().__init__()

        self.name: str = "BNH"

        self.num_dim: int = 2
        self.num_obj: int = 2
        self.num_cstr: int = 2
        self.num_fidelity = 1

        self.tags = [
            "multi-obj",
        ]

        self.bounds = np.array(
            [
                [0, 5],
                [0, 3],
            ]
        )

        self.objective = [
            self.f1,
            self.f2,
        ]

        self.constraints = [
            self.g1,
            self.g2,
        ]

    def f1(self, x):
        return 4 * x[0] ** 2 + 4 * x[1] ** 2

    def f2(self, x):
        return (x[0] - 5) ** 2 + (x[1] - 5) ** 2

    def g1(self, x):
        return (x[0] - 5) ** 2 + x[1] ** 2 - 25

    def g2(self, x):
        return -((x[0] - 8) ** 2) - (x[1] + 3) ** 2 + 7.7


class TNK(BenchmarkProblem):
    def __init__(self):
        super().__init__()

        self.name: str = "TNK"

        self.num_dim: int = 2
        self.num_obj: int = 2
        self.num_cstr: int = 2
        self.num_fidelity = 1

        self.tags = [
            "multi-obj",
        ]

        self.bounds = np.array(
            [
                [0, np.pi],
                [0, np.pi],
            ]
        )

        self.objective = [
            self.f1,
            self.f2,
        ]

        self.constraints = [
            self.g1,
            self.g2,
        ]

    def f1(self, x):
        return x[0]

    def f2(self, x):
        return x[1]

    def g1(self, x):
        return -(x[0] ** 2) - x[1] ** 2 + 1 + 0.1 * np.cos(16 * np.arctan(x[0] / x[1]))

    def g2(self, x):
        return (x[0] - 0.5) ** 2 + (x[1] - 0.5) ** 2 - 0.5


class OSY(BenchmarkProblem):
    def __init__(self):
        super().__init__()

        self.name: str = "OSY"

        self.num_dim: int = 6
        self.num_obj: int = 2
        self.num_cstr: int = 6
        self.num_fidelity = 1

        self.tags = [
            "multi-obj",
        ]

        self.bounds = np.array(
            [
                [0.0, 10.0],
                [0.0, 10.0],
                [0.0, 5.0],
                [0.0, 6.0],
                [0.0, 5.0],
                [0.0, 10.0],
            ]
        )

        self.objective = [
            self.f1,
            self.f2,
        ]

        self.constraints = [
            self.g1,
            self.g2,
            self.g3,
            self.g4,
            self.g5,
            self.g6,
        ]

    def f1(self, x):
        return -(
            25 * (x[0] - 2) ** 2
            + (x[1] - 2) ** 2
            + (x[2] - 1) ** 2
            + (x[3] - 4) ** 2
            + (x[4] - 1) ** 2
        )

    def f2(self, x):
        return np.sum(x**2)

    def g1(self, x):
        return -x[0] - x[1] + 2

    def g2(self, x):
        return -6 + x[0] + x[1]

    def g3(self, x):
        return -2 + x[1] - x[0]

    def g4(self, x):
        return -2 + x[0] - 3 * x[1]

    def g5(self, x):
        return -4 + (x[2] - 3) ** 2 + x[3]

    def g6(self, x):
        return -((x[4] - 3) ** 2) - x[5] + 4


if __name__ == "__main__":
    pass

1	import numpy as np	2✔
2
3	from smt_optim.benchmarks.base import BenchmarkProblem	2✔
4
5
6	class BNH(BenchmarkProblem):	2✔
7	def __init__(self):	2✔
8	super().__init__()	2✔
9
10	self.name: str = "BNH"	2✔
11
12	self.num_dim: int = 2	2✔
13	self.num_obj: int = 2	2✔
14	self.num_cstr: int = 2	2✔
15	self.num_fidelity = 1	2✔
16
17	self.tags = [	2✔
18	"multi-obj",
19	]
20
21	self.bounds = np.array(	2✔
22	[
23	[0, 5],
24	[0, 3],
25	]
26	)
27
28	self.objective = [	2✔
29	self.f1,
30	self.f2,
31	]
32
33	self.constraints = [	2✔
34	self.g1,
35	self.g2,
36	]
37
38	def f1(self, x):	2✔
39	return 4 * x[0] ** 2 + 4 * x[1] ** 2	2✔
40
41	def f2(self, x):	2✔
42	return (x[0] - 5) 2 + (x[1] - 5) 2	2✔
43
44	def g1(self, x):	2✔
45	return (x[0] - 5) 2 + x[1] 2 - 25	2✔
46
47	def g2(self, x):	2✔
48	return -((x[0] - 8) 2) - (x[1] + 3) 2 + 7.7	2✔
49
50
51	class TNK(BenchmarkProblem):	2✔
52	def __init__(self):	2✔
53	super().__init__()	2✔
54
55	self.name: str = "TNK"	2✔
56
57	self.num_dim: int = 2	2✔
58	self.num_obj: int = 2	2✔
59	self.num_cstr: int = 2	2✔
60	self.num_fidelity = 1	2✔
61
62	self.tags = [	2✔
63	"multi-obj",
64	]
65
66	self.bounds = np.array(	2✔
67	[
68	[0, np.pi],
69	[0, np.pi],
70	]
71	)
72
73	self.objective = [	2✔
74	self.f1,
75	self.f2,
76	]
77
78	self.constraints = [	2✔
79	self.g1,
80	self.g2,
81	]
82
83	def f1(self, x):	2✔
84	return x[0]	2✔
85
86	def f2(self, x):	2✔
87	return x[1]	2✔
88
89	def g1(self, x):	2✔
90	return -(x[0] 2) - x[1] 2 + 1 + 0.1 * np.cos(16 * np.arctan(x[0] / x[1]))	2✔
91
92	def g2(self, x):	2✔
93	return (x[0] - 0.5) 2 + (x[1] - 0.5) 2 - 0.5	2✔
94
95
96	class OSY(BenchmarkProblem):	2✔
97	def __init__(self):	2✔
98	super().__init__()	2✔
99
100	self.name: str = "OSY"	2✔
101
102	self.num_dim: int = 6	2✔
103	self.num_obj: int = 2	2✔
104	self.num_cstr: int = 6	2✔
105	self.num_fidelity = 1	2✔
106
107	self.tags = [	2✔
108	"multi-obj",
109	]
110
111	self.bounds = np.array(	2✔
112	[
113	[0.0, 10.0],
114	[0.0, 10.0],
115	[0.0, 5.0],
116	[0.0, 6.0],
117	[0.0, 5.0],
118	[0.0, 10.0],
119	]
120	)
121
122	self.objective = [	2✔
123	self.f1,
124	self.f2,
125	]
126
127	self.constraints = [	2✔
128	self.g1,
129	self.g2,
130	self.g3,
131	self.g4,
132	self.g5,
133	self.g6,
134	]
135
136	def f1(self, x):	2✔
137	return -(	2✔
138	25 * (x[0] - 2) ** 2
139	+ (x[1] - 2) ** 2
140	+ (x[2] - 1) ** 2
141	+ (x[3] - 4) ** 2
142	+ (x[4] - 1) ** 2
143	)
144
145	def f2(self, x):	2✔
146	return np.sum(x**2)	2✔
147
148	def g1(self, x):	2✔
149	return -x[0] - x[1] + 2	2✔
150
151	def g2(self, x):	2✔
152	return -6 + x[0] + x[1]	2✔
153
154	def g3(self, x):	2✔
155	return -2 + x[1] - x[0]	2✔
156
157	def g4(self, x):	2✔
158	return -2 + x[0] - 3 * x[1]	2✔
159
160	def g5(self, x):	2✔
161	return -4 + (x[2] - 3) ** 2 + x[3]	2✔
162
163	def g6(self, x):	2✔
164	return -((x[4] - 3) ** 2) - x[5] + 4	2✔
165
166
167	if __name__ == "__main__":	2✔
NEW 168	pass	×

SMTorg / smt-optim / 28686583443

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