Simulation Optimisation of Laboratory Resources in Universities with Intelligent Scheduling Strategies

This paper establishes a solution model for resource scheduling optimization in university laboratories, and sets the corresponding constraints and objective functions.The genetic algorithm under the heuristic algorithm is used to solve the resource scheduling optimization problem.On this basis, the pyramid model is constructed, the population evolution and variant strategy are proposed respectively, the model genes are labeled with scheduling cost adaptation, and the genes are generated in series.The framework of scheduling algorithm is proposed, and the dynamic scheduler is constructed to realize the scheduling of university laboratory resources.Through simulation experiments and algorithm analysis, the effectiveness of the use of the model is verified.The experimental results show that when the number of simulation is 10 times, the fitness of the population is 20, 100 and 200 respectively.After the implementation of scheduling for college laboratory resources, the utilization rate of laboratory equipment is increased by 16.3%, 34.6% and 18.4% respectively.