Process manufacturing 2 algorithms
Modelling
The problem assumptions and starting data are determined, confirming that the approximation made will provide the expected solution type.
Data
Review the available data and choose the structure that fits the problem.
Design
Design of the algorithm using one of the different problem-solving techniques such as the voracious technique, divide and conquer technique, dynamic programming, linear programming and the use of graphs.
Analysis
Analysis of the algorithm, evaluating its efficience through the maximum number of operations that the algorithm will perform to solve the problem.
Target
Establishment of the objective or multi-objective function that allows the optimal solution to be found from among all possible solutions.
Deployment
Establishing a hyperparameter modification strategy, several tests of the chosen algorithm are carried out with each set of hyperparameters and the one that provides the best result is chosen. A protocol of possible improvements to be implemented in the future and lessons learned is drawn up.
