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Selection of Robot Measurement Configurations
Published in Hanqi Zhuang, Zvi S. Roth, Camera-Aided Robot Calibration, 2018
The Simulated Annealing (SA) approach was adopted in Zhuang, Wang and Roth (1994) to obtain optimal or near optimal measurement configurations for robot calibration. Simulated annealing is a stochastic optimization method derived from Monte Carlo methods in Statistical Mechanics (Kirkpatrick, Gelatt and Vecchi (1983) and Aarts and Korst (1989)). It has been successfully applied to a variety of optimization problems. Extension of the simulated annealing technique include the mean field annealing (Nobakht, Bout, Townsend and Ardalan (1990)) and the tree annealing (Han, Snyder and Bilbro (1990)). The simulated annealing algorithm is very computationally elaborate, though it often provides a better solution.
Multiview Image Matching for 3D Earth Surface Reconstruction
Published in Yuhong He, Qihao Weng, High Spatial Resolution Remote Sensing, 2018
Different strategies have been developed to solve such a local minimum problem based on regularization and Markov random fields, including continuation, simulated annealing, highest confidence first, and mean field annealing methods (Szeliski, 2010). More efficient methods, such as maximum flow and graph cut (e.g., Ishikawa, 2003; Roy & Cox, 1998) have been recently developed. In some sense, the MRF optimization in Equation 5.14 is also an energy minimization function, although the target of Equation 5.14 is to remove ambiguity in multicandidates of points.
Cellular manufacturing design 1996–2021: a review and introduction to applications of Industry 4.0
Published in International Journal of Production Research, 2023
Roohollah YounesSinaki, Azadeh Sadeghi, Hadi Mosadegh, Najat Almasarwah, Gursel Suer
According to Table 5, Safaei, Saidi-Mehrabad, and Jabal-Ameli (2008a) study stands as the top publication in which a SA algorithm was employed to solve the CF problem. They formulated the CF problem as mixed-integer non-linear programming model under dynamic condition. The superiority of their proposed model compares to existed ones is the sequence of operations, alternative process plans for part types, and machine replication was considered to determine the batch inter/intra-cell material handling. The proposed model aimed to minimise the sum of the machine constant and variable costs, inter- and intra-cell material handling, and reconfiguration costs. To solve the model, a hybrid meta-heuristic based on mean field annealing (MFA) and SA was developed. A high-quality initial solution to start the search process in the SA algorithm was generated by employing the MFA. The performance of the proposed algorithm with respect to some performance measures was compared to classical SA and results indicated the outperformance of the proposed method particularly for large-sized problems. The most recent examples of the application of the SA algorithm for CF can be found in Liu, Wang, and Leung (2016a), Rabbani et al. (2017a), Iqbal and Al-Ghamdi (2018), Forghani, Fatemi-Ghomi, and Kia (2020), and Thanh et al. (2016).