Task Scheduling Research Based On The Time Petri Net And The Intelligent Optimization Algorithm

Parallel test that executes multiple testing tasks simultaneously,reduces the equipment idle time,increases utilization rate of equipment resource and then raises the system test efficiency, as the purpose.Optimization scheduling is core issue of the parallel test technology in parallel test task ,Petri net can describe system's sharing,conflict,exclusion,concurrency and indeterminancy, therefore,Petri net theory suits to carrying on the modelling and the analysis of the automated test system.Based on the Petri net theory's foundation,chosing the time Petri net as the modelling tool, the time Petri net maps the time restraint into the transition and takes time as the evaluation parameter of task scheduling efficiency, being widely used in the task scheduling and the time analysis.Decompose test assignment, establish task correlogram, establishment corresponddence time Petri net model according to algorithm.In order to overcome the insufficiency in each algorithm,combine genetic algorithm with Particle Swarm Optimization algorithm, take advantage of the intelligent algorithm's intellectualization sufficiently, introduce the GA-PSO algorithm into the training on the time Petri net model the first time, restraint the transition with time, carry on the optimization to task scheduling's transition sequence, in order to obtain the optimal Scheduling Options speedily.Experimental results show that, on account of the practical task scheduling, the algorithm convergents speedily with greater convergence probability, and the effect is better than geneti c-ant colony algorithm, finally obtained the most ideal optimization transition sequence.