Solving constrained engineering design problems with multi-objective artificial algae algorithm

Abstract

Engineering design problems fall into the category of problems that are very difficult to optimize. Nature-inspired metaheuristic techniques can be beneficial to solve such problems. In this study, a total of 14 different problems, 7 of which are benchmark problems and 7 of which are engineering design problems, were optimized using the recently proposed multi-objective artificial algae algorithm, MOAAA for short. For the performance test of the MOAAA, 4 different metrics named HV, SPREAD, EPSILON and IGD were used. Performance comparison was made with NSGA-II, PAES, MOCell, IBEA and MOVS algorithms which are well known in the literature. The Friedman test was applied to the metrics obtained for all algorithms and the average ranks of each algorithm were calculated. The results show that MOAAA has better performance than other algorithms in 3 of 4 metrics. In addition, the Wilcoxon's test reveals that the results obtained by the MOAAA are significant in the 95% confidence level.