The adopted application meta-model in UML resembles the Kahn Process Network (KPN) model and it is targeted at simulation-based performance evaluation.
In comparison to related work, this is the first proposal that defines transformation between UML activity diagrams and streaming data application workload meta models and successfully adopts it for RTES performance evaluation.
In [14], the application of meta-heuristic for cloud task scheduling on Hadoop is investigated.
The application of meta-learning led to an increase in the values of evaluating parameters.
Figure 3 shows the application of meta-heuristic methods for QAP until 2005 (Loiola et al. [2007]).
This paper aims to investigate the application of meta-heuristic optimisation methods to Network Signal Setting Design.
Application of meta-heuristics has been a dynamic studying interest of the reliability optimization to determine idleness and reliability constituents.
In case of application of meta-heuristics of solving NP-hard problems, tuning of algorithm-specific parameters is essential to obtain near-optimal solutions.
Since the 2000s, the application of meta-heuristic algorithms has focused on a few key fields, particularly reservoir operation, groundwater management, and water distribution network design.
In this paper, a new application of meta-heuristic based on NSGA-II is demonstrated for the proposed tri-objective optimization of SC network considering NPD.
It is suitable for solving the large scale practical problems and lays a foundation for the application of meta-heuristic algorithms in industrial production.
