The test task scheduling problem (TTSP) is an essential issue in automatic test system. In this paper, a new non-integrated algorithm called GASCR which combines a genetic algorithm with a new rule for scheme selection is adopted to find optimal solutions. GASCR is a hierarchal approach based on the characteristics of TTSP because the given problem can be decomposed into task sequence and scheme choice. GA with the non-Abelian (Nabel) crossover and stochastic tournament (ST) selector is used to find a proper task sequence. The problem-specific scheme choice rule addresses the scheme choice. To evaluate the proposed method, we apply it on several benchmarks and the results are compared with some well-known algorithms. The experimental results show the competitiveness of the GASCR for solving TTSP.
CITATION STYLE
Shi, J., Lu, H., & Mao, K. (2016). Solving the test task scheduling problem with a genetic algorithm based on the scheme choice rule. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9713 LNCS, pp. 19–27). Springer Verlag. https://doi.org/10.1007/978-3-319-41009-8_3
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