A Comparative Analysis of Two Multi-objective Evolutionary Algorithms in Product Line Architecture Design Optimization

Abstract

The Product Line Architecture (PLA) design is a multi-objective optimization problem that can be properly solved with search-based algorithms. However, search-based PLA design is an incipient research field. Due to this, works in this field have addressed main points to solve the problem: adequate representation, specific search operators and suitable evaluation fitness functions. Similarly what happens in the search-based design of traditional software, existing works on search-based PLA design use NSGA-II, without evaluating the characteristics of this algorithm, such as the use of crossover operator. Considering this fact, this paper reports results from a comparative analysis of two algorithms, NSGA-II and PAES, to the PLA design problem. PAES was chosen because it implements a different evolution strategy that does not employ crossover. An experimental study was carried out with nine PLAs and results of the conducted study attest that NSGA-II performs better than PAES in the PLA design context.