A novel 3D fruit fly optimization algorithm and its applications in economics. Issue 5 (July 2016)

• Record Type: Journal Article
• Authors: Lin, Wei-Yuan
• Is Part Of: Neural computing & applications. Volume 27:Issue 5(2016)
• Page Start: 1391
• Page End: 1413
• Publication Date: 2016-07
• Subjects: Optimization problems -- Fruit fly optimization algorithm -- Economic models -- General regression neural network -- Financial distress prediction; Neural networks (Computer science) -- Periodicals; Neural circuitry -- Periodicals; Artificial intelligence -- Periodicals; Neural Networks (Computer) -- Periodicals; Réseaux neuronaux (Informatique) -- Périodiques; Réseaux nerveux -- Périodiques; Intelligence artificielle -- Périodiques; 006.32
• DOI: 10.1007/s00521-015-1942-8
• Languages: English
• ISSNs: 0941-0643

Abstract

Abstract 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.