PPT-Placement by Simulated Annealing

Simulated Annealing Simulates annealing process for placement Initial placement Random positions Perturb by block exchanging If Δ cost lt 0 accept otherwise may still accept if const increase is not too much. Moore Professor School of Computer Science Carnegie Mellon University wwwcscmueduawm awmcscmuedu 4122687599 brPage 2br brPage 3br moveset i brPage 4br brPage 5br brPage 6br brPage 7br Idea One Idea Two Idea Three brPage 8br i exp brPage 9br brPage 1 photodetachment. of anionic copper carbonyl clusters in argon matrices. Ryan M. Ludwig, Michael E. Goodrich, . David T. Moore. Chemistry Department, Lehigh University. 69. th. ISMS, Univ. Illinois Urbana-Champaign. 2010-2011. Andry. Pinto. Hugo Alves. Inês Domingues. Luís Rocha. Susana Cruz. Simulated Annealing. Introduction to Simulated Annealing (SA). Meta-Heuristic Concept. Historical Approach. SA Algorithm. By . Rohit. Ray. ESE 251 . The Problem. Most . minimization (maximization) strategies . work to find the nearest local minimum. Trapped at local . minimums (maxima). Standard strategy. Generate trial point based on current estimates. Floor-planning . Based on B∗-Tree and Fast . Simulated Annealing. Paper by Chen T. C. and Cheng Y. . W (2006). Presented . by Gal . Itzhak. 22.7.15. Agenda. Introduction. What . is a Floor-Planning?. Nidia C. Gallego. Robbie a. Meisner. Tim D. . Burchell. Oak Ridge National Laboratory. INGSM-13. Seattle, WA – September 15. , . 2013. Irradiation damage in graphite induces dimensional changes. Polygranular. Daniel Paden Tomasello. Simulated Annealing Algorithm. An approximation algorithm used for global optimization. . In my model, simulated annealing is used to help a robot, which may only detect surrounding elevations, find the highest elevation. (Local Search). and . Robust . Scalable Data mining . for . the Data Deluge . Petascale Data Analytics: Challenges, and Opportunities (PDAC-11. ). Workshop at SC11 Seattle. November 14 2011. Geoffrey Fox. gcf@indiana.edu. What is it?. Simulated Annealing is a . stochastic optimization . method that derives its name from the annealing process used to re-crystallize metals. Comes under the category of evolutionary techniques of optimization. Matthew Kelly. April 12, 2011. What is Annealing?. Slow cooling of a heated substance allows atoms to line themselves up, creating a stronger structure with minimum energy. Accelerating the cooling process produces a structure with more energy and fewer atoms optimally aligned.. Rohit. Ray. ESE 251 . The Problem. Most . minimization (maximization) strategies . work to find the nearest local minimum. Trapped at local . minimums (maxima). Standard strategy. Generate trial point based on current estimates. :. Idea: . Always follow the best neighbor. Pros: . Easy to implement; performs well in convex spaces. Cons: . Gets stuck in local-maximum; lost in plateaus; ridges . Local-Maximum. Global-Maximum. Valley. Employ randomness strategically to help explore design space. Randomness can help escape local minima. Increases chance of searching near the global minimum. Typically rely on . pseudo-random number generators . Likelihood Methods in Ecology. Jan. 30 – Feb. 3, 2011. Rehovot. , Israel. Parameter Estimation. “The problem of . estimation. is of more central importance, (. than hypothesis testing. )... . for in almost all situations we know that the .