Natural Obstacles and Biological Salmon Behaviors Link to Modelling Approaches of Computational Intelligence Procedures for the Standard System

Abstract

Since classical mathematical approaches have been applied to many technical and theoretical problems, they are useful and accurate for searching solutions even they suffer from large systems and multi spaces. Recently, many algorithms have been proposed for introducing new approaches conducted to phenomena or entities in nature. Many biological behaviors and mechanisms are adopted to replace classical methods which are presented in various names as performed for the natural inspiration. In these works, the novel computational intelligence is explored in Artificial Salmon Tracking Algorithm (ASTA). ASTA is developed based on the natural obstacles and biological Salmon behaviors link to modeling approaches of computational intelligence procedures. Moreover, ASTA is applied to a standard system model considering environmental requirements for the global warming parameter. The system process is supported by suppliers to fulfill a sustainable operation while the productions are also subjected to reach clean and green targets. In these studies, ASTA is also used to optimize the system and to get an optimal portion of the balanced combination of the system results. The biological Salmon behavior presented in ASTA is also tested based on technical requirements; the results show that the solution is produced dynamically to feed the operation. The system model is balanced in various combination portions of the solution while ASTA has been demonstrated clearly to search for optimal solutions.