Simulated Annealing (SA) for Mathematical Optimization

Lately, I have been having conversations with various people regarding simulated annealing (SA). I thought that it would be helpful to put all the references in 1 spot.

I am not an expert in the subject. I am just trying to become part of the conversation.

Below are some references for SA which you hopefully will find helpful.

1. Generally Applicable References
   
   1. Books
      
      1. Annealing Algorithm by R.H.J.M Otten and L.P.P.P van Ginneken
         
         1. Amazon
            
      2. Introduction to Optimum Design, Third Edition by Jasbir Arora
         
         1. Amazon
            
         2. ASCE Library
            
         3. Elsevier
            
         4. Google
            
      3. Numerical Recipes 3rd Edition: The Art of Scientific Computing by William H. Press, Saul A. Teukolsky
         
         1. Amazon
            
      4. Simulated Annealing and Boltzmann Machines: A Stochastic Approach to Combinatorial Optimization and and Neural Computing by Emile Aarts, Jan Korst
         
         1. Interesting how book suggests using Boltzman Machines to execute SA in parallel. Also, please remember that Boltzman Machines are part of the mathematical stack for deep learning.
            
         2. Amazon
            
      5. Simulated Annealing: Strategies, Potential Uses and Advantages by Marcos Tsuzuki, Thiago De Castro Martins
         
         1. Amazon
            
      6. Simulated Annealing: Theory and Applications by P.J. van Laarhoven, E.H. Aarts
         
         1. Amazon
            
   2. Articles
      
      1. Equation of State Calculations by Fast Computing Machines by Nicholas Metropolis, A. Rosenbluth, ... - Journal of Chemical Physics - Volume 21, Number 6 - June 1953
         
   3. Internet Information
      
      1. Serial and Parallel Simulated Annealing and Tabu Search Algorithms for the Traveling Salesman Problem by Miroslaw Malek, Mohan Guruswamy, Mihix Pandya, Howard Ownes
         
      2. Simulated Annealing by CryptoDen
         
      3. Simulated Annealing by Nathan Germer
         
      4. Simulated Annealing Tutorial - ME575 - Optimization
         
      5. Stony Brook Algorithm Repository by Steven Skiena
         
      6. Wikipedia
         
         1. Adaptive Simulated Annealing
            
         2. Simulated Annealing
            
   4. Python
      
      1. Basics of Simulated Annealing in Python by StackOverFlow
         
      2. Python module for Simulated Annealing optimization by perrygeo
         
      3. Python Scientific Lecture Notes - ... - Simulated Annealing
         
      4. scipy.optimize.anneal
         
2. Parallelizing SA References
   
   1. Books
      
      1. Simulated Annealing and Boltzmann Machines: A Stochastic Approach to Combinatorial Optimization and and Neural Computing by Emile Aarts, Jan Korst
         
         1. Interesting how book suggests using Boltzman Machines to execute SA in parallel. Also, please remember that Boltzman Machines are part of the mathematical stack for deep learning.
            
         2. Amazon
            
   2. Articles
      
      1. Efficient implementation of parallel simulated annealing algorithm in GPUs by A. M. Ferreiro, J. A. García, J. G. López-Salas, C. Vázquez
         
      2. Implementing a Parallel Simulated Annealing Algorithm by Zbigniew J. Czech, Wojciech Mikanik, Rafał Skinderowicz
         
      3. Mutlithreaded Simulated Annealing by Leonardo Jelenković, Joöko Poljak
         
      4. Parallel Simulated Annealing Algorithm for Graph Coloring Problem by Szymon Łukasik, Zbigniew Kokosiński, and Grzegorz Świętoń
         
      5. Parallel Simulated Annealing Algorithms by D. Janaki Ram, T. H. Sreenivas, K. Ganapathy Subramaniam
         
      6. Parallel Simulated Annealing Library by University of Paderborn
         
      7. Serial and Parallel Simulated Annealing and Tabu Search Algorithms for the Traveling Salesman Problem by Miroslaw Malek, Mohan Guruswamy, Mihix Pandya, Howard Ownes