INFORACTIVE
Platform Philosophy

Enterprise using genetic algorithm
(genetic algorithm)
Planning & SimulationTool

INFORACTIVE
Reinforced Genetic Algorithm
Foundation platform

Charles Darwin

“In the end, the species that survives is not the strong species or the intelligent species. Strongly, the species that survives is the one that adapts best to change.”

찰스 다

"결국 살아 남는 종은 강인한 종도 아니고, 지적 능력이 뛰어난 종도 아니다. 종국에 살아 남는 것은 변화에 가장 잘 적응하는 종이다.“
Genetic Algorithm = Genetic Algorithm
What is a genetic algorithm Imitating the evolutionary system of the natural world metaheuristic algorithmsUsed to solve complex optimization problems with”,
deep learning Set initial weights, and machine learning It can be used to solve problems, INFORACTIVE PLATFORM Top In-house manufacturing, production, sales, and cost optimization scheduling using generative AI
(= Enterprise P Lanning & Simulation)
Use as an ideological basis for derivation

INFORACTIVE

Oilfield Using algorithms
Management decisions for all companies
Planning & Simulation through the “INFORACTIVE Platform”

It differs from general data analysis in concept.

Parameter Definition

Genetic algorithm flowchart

Define parameters for
genetic algorithms

(Set initial deep learning values)
How to express a generation
Matrix structure binary vector
Select the largest number of households
Generation N (parent to child n generation)
End conditions
Run the algorithm until the maximum number of generations is reached
Selection of numbers, including by household
For example, selected as 20 per generation
Cross operator settings
1-point intersecting arithmetic
Mutation operators
Flipbit calculation
(Derive optimal function after iteratively modifying vector elements)
Cross ratio
Fit function
Functional equations (0 if constraints are not satisfied)
Mutation rate selection
For example, select a Mutant object ratio of 20%

Global optimization values

The function F (x) is the minimum value of F (x) according to the X value
When it comes to (in other words, optimization values), it is almost always impossible to draw the above graph itself. (It is also very common for differentiation itself to be impossible)
purchasing, production, Sales areas, logistics optimization, lead time optimization, cost simulation.
Having the ability to optimize and functionally implement techniques is important.

Data that mostly exists in ERP system.

Deriving optimization values through Python function coding

Best Solution

INFORACTIVE
Simulation

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