Many-Objective Optimization in Search-Based Software Engineering (SBSE)
SBSE (Search-Based Software Engineering) work has been widely increased in the past few timespans. Search-based optimization heuristic algorithms are introduced forresolving the issues in software engineering areas. SBSE can be applied to all the issues state right from the requirement analysis phase tothe testing, maintenance, and re-engineering phase.
There is a vast subsystem of optimization under many-objective optimization which has high significance in real-time issues, such as development and design in software engineering.
Since the last few years, a huge set of multi-objective optimization for empirical algorithms has been introduced. Few of them have been implemented in various software quality products which inhibits flexible and secure features. This research paper includes the analysis and execution phase of heuristic algorithms for multi-objective optimization. This has been examined that using the same empirical search algorithm in unique ways interprets different results for software programs. Thus, due to this the structure of the algorithms has been affected as well it impacts the process implementation. Also, this paper states algorithm based on elitist NSGA-II(non-dominated sorting genetic algorithm) is analyzed to overcome the software problems.
Keywords - Search-based modularization, NSGA-II (non-dominated sorting genetic algorithm), Multi-objective optimization, Many-objective optimization.