A Novel Discrete Fruit Fly Optimization Algorithm for Intelligent Parallel Test sheets Generation
1 College of Media and Communication, Liaocheng University, Liaocheng, Shandong, China
2 College of Computer Science, Liaocheng University, Liaocheng, Shandong, China
* Corresponding author: email@example.com
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.
Key words: parallel test sheets generation / discrete fruit fly optimization algorithm / computer-aided testing system / combinational optimization
© Owned by the authors, published by EDP Sciences, 2015
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.