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X.-M. Hu and J. Zhang, “An Intelligent Testing System Embedded with an Ant Colony Optimization Based Test Composition Method,” IEEE Congress on Evolutionary Computation, Trondheim, 18-21 May 2009, pp. 1414-1421.

has been cited by the following article:

• TITLE: The Research of Examination Paper Generation Based on Index System Metrics and Multi-Objective Strategy

  AUTHORS: Yan Li, Ji-Qiang Tang

  KEYWORDS: Generating Examination Paper with Computer; Multi-Objective Strategy; Genetic Algorithm

  JOURNAL NAME: Journal of Software Engineering and Applications, Vol.5 No.8, August 28, 2012

  ABSTRACT: Since the examination paper generated with computer by the algorithms of random and backtracking takes on inferior quality and inefficient, and the question of generating examination paper with computer has the character of multi-ob-jective because of the index system metrics, the genetic algorithm with multi-objective strategy optimization is proposed to solve this problem. Mapping the index system to multi-objective functions and optimizing the computing with multi-objective strategy are employed in the algorithm. The genetic algorithm experiment based on the multi-objective strategy optimization shows that the result has the advantages getting tradeoff between performance and quality, and having the ability to tune the performance and quality to meet the user’s requirements.