Mixed Fruit Fly Optimization Algorithm Based on Lozi's Chaotic Mapping

Abstract

Mixed Fruit Fly Optimization Algorithm LGM-FOA (Logistic Mapping-FOA) is an improved mixed fruit fly algorithm on the basis of the Logistic map, but the algorithm was showing an ideal state about convergence precision and stability in the optimization process, because there are three discontinuous points from the Logistic map. To solve this problem, the author proposed a new mixed fruit fly algorithm. The algorithm uses the Lozi's map to have a global search for the optimal parameter values instead of Logistic map. It uses the value as the center to do tiny fluctuations to obtain Final optimal value of quadratic optimization, and improves the initial value selection method of LGM-FOA. In support of the simulation between vector machine regression forecast and the original Fruit Fly Algorithm, Particle Swarm Optimization (PSO), LGM-FOA, the result testifies that the convergence accuracy of this new mixed fruit fly algorithm has obvious advantages.