Optimizing the Multi-UUT Parallel Test Task Scheduling Based on Multi-objective GASA

Parallel test is a new important feature of the future ATS (automatic test system). The optimized parallel test task scheduling is a key problem to the parallel test. In this paper, the genetic algorithm and simulated annealing algorithm are combined effectively to find the multi-UUT (unit-under-test) parallel test tasks array to suffice multiple objectives. The mathematical model and multiple objectives of the multi-UUT parallel test task scheduling are put forward first. Then the gene coding and genetic annealing operating methods are introduced. The result of simulation shows that the algorithm is feasible and efficient.