Even a timber factory that receives orders to supply a certain number of pieces of wood. The goal is to make the best use of the factory's current stock of wood so that the stock remaining after removing the pieces of order can be reused on a subsequent order without losing a large area of wood. This practically means that pieces of wood left after cutting should be as solid as possible.
- Particle Swarm Optimization, PSO with dynamic neighborhood topology
- Differential Evolution, DE with global and local neighborhood topologies
You can install them using:
- matplotlib
pip install matplotlib
- numpy
pip install numpy
- numpy
- https://github.com/Toblerity/Shapely. (The package is based on the GEOS C ++ library, which must be installed)
pip install Shapely
or
conda install -c ”conda-forge” shapely
- Noisyopt: A python library for optimizing noisy functions (https://github.com/andim/noisyopt)
pip install noisyopt
- https://pypi.org/project/descartes/ . (Use geometric objects as matplotlib paths and patches)
pip install descartes
or
conda install -c conda-forge descartes
`
Each folder has a readme on how to run the programs
- Giorgos Tsalidis - LinkedIn
This project is licensed under the MIT License - see the LICENSE.md file for details
[1] S. K. Mylonas, D. G. Stavrakoudis, J. B. Theocharis, and P. A. Mastorocostas, “A Region-Based GeneSIS Segmentation Algorithm for the Classification of Remotely Sensed Images,” Remote Sensing, vol. 7, no. 3, pp. 2474–2508, Mar. 2015. Online link: http://www.mdpi.com/2072-4292/ 7/3/2474 (page 1)
[2] S. Das, A. Abraham, U. Chakraborty, and A. Konar, “Differential Evolution Using a Neighborhood-Based Mutation Operator,” IEEE Transactions on Evolutionary Computation, vol. 13, no. 3, pp. 526–553, Jun. 2009. (page 3)
[3] S. Das and S. Sil, “Kernel-induced fuzzy clustering of image pixels with an improved differential evolution algorithm,” Information Sciences, vol. 180, no. 8, pp. 1237–1256, Apr. 2010. Online link: http://www.sciencedirect.com/science/article/pii/S0020025509005192 (p. 3)
[4] M. Dorigo and T. Stützle, Ant Colony Optimization, ser. Bradford Books. Cambridge, MA, USA: MIT Press, Jun. 2004. (page 6)