Table 2 OBL integrated with metaheuristics and their applications to the engineering optimization problem
Author(s) [Ref.] | Year of publication | Learning method | Application area | Major findings of the study |
|---|---|---|---|---|
Tizhoosh (2005) | 2005 | OBL for ML | Basic concept of OBL | OBL found influential while included in existing ML and improved ANN learning |
Mahdavi et al. (2018) | 2018 | Survey on OBL | Surveyed on different applications of OBL | A rigorous survey of 380 research articles showed that OBL can potentially be used with soft computing techniques |
Shekhawat and Saxena (2020) | 2020 | ICSA, improved Crow search algorithm with OBL | Two benchmarks set of functions, CEC-2017, structural design, frequency wave synthesis and Model Order Reduction problems | The improved version exhibited competitive performance over contemporary optimization methods |
Elaziz and Oliva (2018) | 2018 | OBL for improvement of search space of whale optimization algorithm | Different benchmark functions and parameter estimation of solar cells diode model | OBL helped in improving the exploration capability of WOA and performed better than other competitive models |
Elaziz and Oliva (2017) | 2017 | Improved Sine–Cosine algorithm with OBL | Solving benchmark functions | OBL amended the search ability of SCA. The proposed method achieved better convergence and accuracy |
Tubishat et al. (2020) | 2020 | Improved Salp swarm algorithm with OBL and Local search algorithm | 18 datasets from UCI for feature selection | OBL helps in population diversity of Salp Swarm algo. And Local search algo. Improved the exploration capacity of Salp Swarm algo |
Pradhan et al. (2018) | 2018 | OGWO-opposition based grey wolf optimization | Economic dispatch problem | OBL accelerated the convergence of grey wolf optimization, reduced the computational cost |
Jain and Saxena (2019) | 2019 | OB-MFO: oppositional concept-based moth flame optimization | CEC-2017 benchmark functions, volatility and market power analysis of energy data | Effectiveness of OB-MFO has been suggested. Proposed method is more profitable and can be a potential tool |
Demirören et al. (2021) | 2021 | ObAEF – oppositional concept based AEFA | FOPID controller design for unstable magnetic ball suspension system | ObAEF method performed better to other computationally and statistically |
Ekinci et al. (2020) | 2020 | OBL with atom search optimization (OBASO) | Estimating parameters of automatic voltage regulator system | Superior control performance of OBASO over classical methods in estimating AVR parameters |
Ibrahim et al. (2019) | 2019 | OBL with social spider optimization | Feature selection and classification problem | Effective selection of relevant features and improved the search ability of base optimizer |
Bao et al. (2019) | 2019 | OBL with Dragonfly algorithm (OBLDA) | Multilevel thresholding color image segmentation | Proposed method got high accuracy and stability |
Kar et al. (2016) | 2016 | OBL with GA | Financial time series forecasting | OBGA trained ANN produced lower MAPE than standalone GA trained ANN |
Dash et al. (2021b) | 2021 | Quasi opposition-based Rao algorithm for ANN training (QORA-ANN) | Cryptocurrency prices prediction | Proposed model produced reduced prediction error compared to traditional optimization of ANN |
Zhou et al. (2017) | 2017 | Opposition based memetic search (OBMA) | 80 large benchmarks with 2000–5000 instances from the literature on maximum diversity problem | OBMA established suitable balance between exploration and exploitation and found improved best solutions |
Yildiz et al., (2022) | 2022 | OBL with grasshopper optimization algorithm | Engineering optimization problems | The OBL helped in enhancing performance of grasshopper optimization algorithm |