Constraint-Guided Methods with Evolutionary Algorithm for the Automatic Test Task Scheduling Problem

The automatic test task scheduling problem is a key challenge for automatic test system to improve throughput and reduce test time. The constrained Test task scheduling problem （TTSP） contains network precedence constraint relationships between tasks. Constrained optimization and topological sorting...

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Veröffentlicht in:	电子学报：英文版 2014-07, Vol.23 (3), p.616-620
1. Verfasser:	LU Hui NIU Ruiyao
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Sprache:	eng
Schlagworte:	引导拓扑排序测试任务约束优化自动测试系统调度问题进化算法非支配排序遗传算法
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container_title	电子学报：英文版
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creator	LU Hui NIU Ruiyao
description	The automatic test task scheduling problem is a key challenge for automatic test system to improve throughput and reduce test time. The constrained Test task scheduling problem （TTSP） contains network precedence constraint relationships between tasks. Constrained optimization and topological sorting are applied to handle the constraints. A chaotic non-dominated sorting genetic algorithm is used to stress exploitation ability and obtain high quality solutions. For two commonly applied realworld instances, comparisons show that topological sorting performs much better than constrained optimization and some existing algorithms. Simulation results demonstrate the effectiveness of CNSGA combined with topological sorting for solving constrained TTSP with multiobjectives.
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subjects	引导拓扑排序测试任务约束优化自动测试系统调度问题进化算法非支配排序遗传算法
title	Constraint-Guided Methods with Evolutionary Algorithm for the Automatic Test Task Scheduling Problem
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