PPT-Simulated Annealing 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. 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. 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. Jong Youl Choi, Judy . Qiu. , Marlon Pierce, and Geoffrey Fox. School of Informatics and Computing. Pervasive Technology Institute. Indiana University. S. A. L. S. A. project. . http://. salsahpc.indiana.edu. 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. Presented by Donna Burge-Tetrick, Ph.D.. Facts Every Educational . Stakeholder Should Know. Approximately . 70% . of US jobs don’t require a four-year degree. . Two-Thirds. . of the . fastest-growing. Annealing . Dimension Reduction. and Biology. Indiana University. Environmental Genomics. April 20 2012. Geoffrey Fox. gcf@indiana.edu. . . http://www.infomall.org. . http://www.futuregrid.org. SOAKING OR HOLDING. CONTROLLED COOLING . HEATING CYCLE. 3. FINE PEARLITE . Rc 40. COARSE PEARLITE . RC 15. VERY FINE PEARLITE . Rc 60. MARTENSITE . Rc 64. FURNACE COOL. AIR COOL. OIL QUENCH. WATER QUENCH. Chapter 3 covered problems that considered the whole search space and produced a sequence of actions leading to a goal.. Chapter 4 covers techniques (some developed outside of AI) that don’t try to cover the whole space and only the goal state, not the steps, are important. . 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 . . Liliana Teodorescu. . Physics vs Computer Science/Engineering. P. hysics. . and . Computer Science/Engineering . have . long . established . mutually . beneficial links. Computer Science/Engineering to Physics.