This project involves using Genetic Algorithm to solve the dynamic scheduling problem of flexible Job Shop production.
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Updated
Mar 31, 2023 - Python
This project involves using Genetic Algorithm to solve the dynamic scheduling problem of flexible Job Shop production.
python-lekin: Flexible Supply Chain Planning and Scheduler
SEAGE (Search Agents) is a hyper-heuristic framework for metaheuristic collaboration.
Job Shop Scheduling metaheuristics
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Learning how to implement GA and NSGA-II for job shop scheduling problem in python
Job-Shop Scheduling Problem with Mixed Integer Optimization. Formulation and implementation in Julia Gurobi.
In the context of optimizing the production of a fully connected "smart" 3d printers factory, machine learning methods like Genetic algorithms, Deep Neural Networks as well as more traditional algorithms like Job-shop were used in a simulation environment (Robotic Operating System).
Code used in 2015 paper "Solving Variants of the Job Shop Scheduling Problem Through Conflict-Directed Search". Code using old version of Mistral solver (https://homepages.laas.fr/ehebrard/mistral.html), and old version of IBM ILOG CP Optimizer (https://www.ibm.com/products/ilog-cplex-optimization-studio/cplex-cp-optimizer).
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