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A reusable implementation of the Simulated Annealing metaheuristic for optimization problems Installation: 1. Run build.bat (creates dist/ folder if absent) 2. Change to dist/ and unpack compressed distribution 3. Change to unpacked distribution folder 4. run: setup.py install This will install the simaneal package to Libs/site-packages Files: MANIFEST.in - Defines what will be in the final installer tarball README - This file runner - Python script to import this application's modules and launch setup.py - distutil setup file simanneal/ - Simulated Annealing Package __init__.py - Used by distutils to find the package root, should be empty Annealer.py - Core implementation samples/ - Sample package __init__.py - Used by distutils to find the package root, should be empty samplebase.py - Base class for samples, implements some simple defaults, children should only override what changes trivial.py - Sample of using Annealer to optimize a small one-dimensional array twodimensional.py - Sample of using Annealer to optimize a small two-dimensional array threedimensional.py - Guess what this does. visualizer.py - tkinter-based visualizer with threading for Annealer results (reusable for other data) tests/ - Unit tests Annealer.py - Unit tests for the core Annealer module twodimensional.py - Unit tests for Sample, as implemented in twodimesional (yeah, unusual)
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Simple Python Simulated Annealing Implementation
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