A Novel Discrete Fruit Fly Optimization Algorithm for Intelligent Parallel Test sheets Generation

• Published in: MATEC Web of Conferences Vol. 22; p. 1040
• Main Authors: Wang, Fengrui, Wang, Wenhong, Dong, Jinxin, Feng, Tianmin
• Format: Journal Article Conference Proceeding
• Language: English
• Published: Les Ulis EDP Sciences 01.01.2015
• Subjects: combinational optimization; Computer simulation; computer-aided testing system; discrete fruit fly optimization algorithm; Evolutionary algorithms; Optimization algorithms; parallel test sheets generation; Particle swarm optimization
• ISSN: 2261-236X; 2274-7214; 2261-236X
• DOI: 10.1051/matecconf/20152201040

Parallel test sheet generation (PTSG) is a NP-hard combinational optimization problem, in which test sheet generation algorithm with high quality and efficiency is the core technology. Basic fruit fly optimization algorithm (FOA) has the defects of easily relapsing into local optimal and low convergence precision when solving PTSG problem. In this paper, a novel discrete fruit fly optimization algorithm is proposed to solve the PTSG problem, in which a discrete osphesis searching operator based on the problem-specific knowledge is designed to help the FOA escaping from being trapped in local minima. To evaluate the performance of the proposed algorithm, the simulation experiments were conducted using a series of item banks with different scales. The superiority of the proposed algorithm is demonstrated by comparing it with the particle swarm optimization algorithm and differential evolution algorithm.