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This repo encapsulates a Python implementation of the Simulated Annealing Algorithm to solve by means of a "minimum energy state" heuristic the NP-hard n-machines|no preemption|C_max job shop scheduling problem, considering n=2 machines and jobs having release dates. The code was designed and wrote by me. The whole heuristic design, complexity analysis, optimization, and ideas were made possible by team-working with Arianna Montironi and Chiara Panetta. The developed heuristic is the final deliverable of our project work held during the Quantitative Methods for Decision Aid 2021 Class in Politecnico di Torino.

License: MIT License

Python 100.00%
heuristics simulated-annealing algorithms complexity-theory scheduling-problem python np-hard combinatorial-optimization object-oriented-programming probabilistic-models

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