The properties of an object define attributes and
operating characteristics, which explore and govern default values.
1- Each
object can consist of specific Genetic Principles and unique inheritance
patterns.
2- Genetic
Principles are comprehensive techniques for solutions and optimization of
problems.
3- They are based
on the natural selection of Genetic Algorithms and pattern-matching mechanisms
within an object.
4- Systems Owners can develop
Genetic Algorithms within the Input Framework.
5- It
ensures Harmonic Balance within the designated System platform.
The genetic Algorithm provides infrastructure support to Data Resources
within the Input Framework and all resources (internal and external) in the system platform.
Encapsulated Genetic Algorithms within Input can
generate optimal resources and cause sustainable process operations.
A genetic Algorithm builds and instantiates Input
Parameters within objects and optimizes all resources through an Information
Processing System.
Moreover,
the Genetic Algorithm provides standards and guidelines for quality Outputs.
Genetic Algorithms can establish vital extension
facilities for the system platform to meet operational and functional
requirements.
Input 1 with encapsulated Genetic Algorithm generates Output1 with
Genetic Algorithm pattern. By the rules of analogy, similarity can exist
between Input 1 and Output 1 properties. The genetic Algorithm (Conventional
Algorithm) within the Input 1 Framework optimizes all resources and system
performances. Besides, it can set realistic goals. Output 1 can accomplish more
comprehensive coverage of complex parameters than the “Unconventional
Algorithm” within the system platform. Eventually, the outcome mapping for
the encapsulated Genetic Algorithm shows a Closed-loop model structure. (Fig 1)
System Owner develops an “Unconventional Algorithm” for solving complex
scenarios in the rationalization process. Input 2 data with an Encapsulated
Unconventional Algorithm can process the Output 2 framework through the Information
Processing System. Transparent Analogical Patterns between Input 2 and Output 2
can identify allocated Unconventional Algorithms.
Unconventional Algorithm focuses on instance parameters of complexity in
the rationalization process. Individualistic Algorithms would fail to respond
to internal and external resources. Besides, it could hardly perceive and define functional and operational strategy requirements. Ultimately,
outcome mapping for encapsulated Unconventional Algorithms generates a partial
Open-loop Structure Model. Parameter Complexity might require multiple
suboptimizations on the evolutionary path of systems performances. (Fig1)