A novel 3D fruit fly optimization algorithm and its applications in economics

作者：Lin, Wei-Yuan^*

来源：Neural Computing & Applications, 2016, 27(5): 1391-1413.

DOI：10.1007/s00521-015-1942-8

• Optimization problems
• Fruit fly optimization algorithm
• Economic models
• General regression neural network
• Financial distress prediction

Fruit fly optimization algorithm (FOA) is a method that we have previously developed from the food-finding behavior of fruit flies to solve optimization problems. The advantage of FOA is simple and easy to understand compared to traditional stochastic algorithms. In this paper, we propose a modified algorithm called novel 3D-FOA. The performances of the 3D-FOA are far better than those of the original FOA. We select more than thirty different nonlinear functions as test vehicles to show that the search efficiency and/or quality of the 3D-FOA is superior to that of the genetic algorithm and particle swarm optimization algorithm. We also apply the 3D-FOA on some economics topics, two theoretic examples and a case study. Our results strongly suggest that the 3D-FOA can enhance capabilities in a variety of fields and future experiments.

• 出版日期2016-7
• 单位苏州大学