Research problems in Search-Based Software Engineering for many-objective optimization
Syed Zaffar Qasim, Muhammad Ali Ismail · 2017
A large number of design or decision making problems, in engineering and management, require simultaneous optimization of multiple and often conflicting objectives. Although the current state-of-the-art algorithms (NSGA II and SPEA2) have been proved quite efficient for solving two- and three-objective problems, the performance of these algorithms is unacceptable for solving many-objective problems which are the problems with four or more objectives. This paper is a thorough survey of the potential many-objective optimization problems in the field of Search-Based Software Engineering (SBSE) that need more efficient and robust algorithms than the current state-of-the-art techniques. SBSE studies the application of meta-heuristic optimization techniques to software engineering problems. While discussing the various SBSE problems, we mention the contemporary solution approaches for optimizing them along with their deficient areas that need further improvement. Finally, in the conclusion part, the promising research directions for many-objective optimization are highlighted for further motivation and encouragement of the readers of this text.