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DaRUS

(University of Stuttgart)

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Publication Year: 2024

11 to 20 of 47,256 Results

GP_03.json Mar 17, 2025 - Replication Data for: Optimizing an expensive multi-objective building performance problem: Benchmarking model-based optimization algorithms against metaheuristics with and without surrogates. JSON - 546.2 KB - MD5: 7a0b79d1f887ac6dd9ce1c7d75fa8b28
GP_04.json Mar 17, 2025 - Replication Data for: Optimizing an expensive multi-objective building performance problem: Benchmarking model-based optimization algorithms against metaheuristics with and without surrogates. JSON - 555.3 KB - MD5: cce918a488a3074f5ab1ba3d0fe7b344
LHS_00.json Mar 17, 2025 - Replication Data for: Optimizing an expensive multi-objective building performance problem: Benchmarking model-based optimization algorithms against metaheuristics with and without surrogates. JSON - 1.3 MB - MD5: a6cbae1b4477d3e08c2775ccf15d5c68
LHS_01.json Mar 17, 2025 - Replication Data for: Optimizing an expensive multi-objective building performance problem: Benchmarking model-based optimization algorithms against metaheuristics with and without surrogates. JSON - 7.0 MB - MD5: 0287865a26350178b258a19a9103dc6a
MOEAD_00.json Mar 17, 2025 - Replication Data for: Optimizing an expensive multi-objective building performance problem: Benchmarking model-based optimization algorithms against metaheuristics with and without surrogates. JSON - 556.5 KB - MD5: 00ced999c97245139b970e7b95765ce5
MOEAD_01.json Mar 17, 2025 - Replication Data for: Optimizing an expensive multi-objective building performance problem: Benchmarking model-based optimization algorithms against metaheuristics with and without surrogates. JSON - 6.6 MB - MD5: 7e6985db79cb7fa0a1262ff2dcd593e5
MOEAD_01.json Mar 17, 2025 - Replication Data for: Optimizing an expensive multi-objective building performance problem: Benchmarking model-based optimization algorithms against metaheuristics with and without surrogates. JSON - 555.2 KB - MD5: 776010318b2b44e4fa31de971639b9a2
MOEAD_02.json Mar 17, 2025 - Replication Data for: Optimizing an expensive multi-objective building performance problem: Benchmarking model-based optimization algorithms against metaheuristics with and without surrogates. JSON - 553.6 KB - MD5: 980db3dfa367ac08537a02cb4bf6764d
MOEAD_02.json Mar 17, 2025 - Replication Data for: Optimizing an expensive multi-objective building performance problem: Benchmarking model-based optimization algorithms against metaheuristics with and without surrogates. JSON - 6.5 MB - MD5: 999a1f4db8ba49a00a49af22338fb69e
MOEAD_03.json Mar 17, 2025 - Replication Data for: Optimizing an expensive multi-objective building performance problem: Benchmarking model-based optimization algorithms against metaheuristics with and without surrogates. JSON - 556.6 KB - MD5: 7d0d7ebfd897e169d1a82fe3f1a82bad

GP_03.json

Mar 17, 2025 - Replication Data for: Optimizing an expensive multi-objective building performance problem: Benchmarking model-based optimization algorithms against metaheuristics with and without surrogates.

JSON - 546.2 KB -

GP_04.json

Mar 17, 2025 - Replication Data for: Optimizing an expensive multi-objective building performance problem: Benchmarking model-based optimization algorithms against metaheuristics with and without surrogates.

JSON - 555.3 KB -

LHS_00.json

Mar 17, 2025 - Replication Data for: Optimizing an expensive multi-objective building performance problem: Benchmarking model-based optimization algorithms against metaheuristics with and without surrogates.

JSON - 1.3 MB -

LHS_01.json

Mar 17, 2025 - Replication Data for: Optimizing an expensive multi-objective building performance problem: Benchmarking model-based optimization algorithms against metaheuristics with and without surrogates.

JSON - 7.0 MB -