Multi-objective Sunflower Optimization (MOSFO)

MOSFO is a novel and powerfull meta-heuristic algorithm for global multi-objective optimization

🌻 The MOSFO algorithm mimics the phototropic life cycle of sunflowers around the sun.

🔍 The proposed algorithm was compared with ten other powerful algorithms: MOGWO, MOPSO, NSGA-II, MOEA/D, NSGA-III, CCMO, ARMOEA, ToP, TiGE 2, and AnD.

📈 Inverted General Distance, Spacing, Maximum Spread, and Hypervolume were used as comparison metrics to evaluate the convergence and coverage capabilities of the algorithms. MOSFO had the best average IGD value in 8 of the 10 test functions when compared with the other algorithms. In terms of MS, MOSFO had the highest average value of MS for 7 of the test functions.

💡 In summary, MOSFO showed substantial convergence and coverage capabilities and proved to be very competitive among the algorithms used, which were carefully selected to be popular and recent. The method is even more promising for problems with three or more objectives.

🔗 This is the source codes of the paper: Multi-objective sunflower optimization: A new hypercubic meta-heuristic for constrained engineering problems, Expert Systems, 2023, https://dx.doi.org/10.1111/EXSY.13331