Modular Test and Simulation of Intelligent Optimization Algorithm
Many problems in life and engineering applications can be attributed to multi-objective optimization problems with contradictory objectives,which have strong application requirements and strong theoretical innovation,and then the model establishment is difficult and the solution methods are complex.In this paper,a modular test and simulation method for intelligent optimization algorithms is proposed.Taking multi-objective particle swarm optimiza-tion as an example,through the parameter configuration experiments of the algorithm itself,as well as the comprehen-sive comparison experiments of multi-test functions and multi-algorithms,the Pareto of Fronts of the algorithm and the convergence and distribution indicators can be obtained.Then,the performance of the algorithm for solving similar optimization problems can be judged.Finally,the multi-objective optimization algorithm is applied to the planning of the tunneling cutting path in the underground coal mine,and the optimal cutting path with high efficiency and strong safety is obtained.Intelligent optimization algorithms can be used to analyze and solve multi-objective optimization problems in the classroom teaching of"artificial intelligence"related courses,and can also be used for experimental teaching demonstrations and innovative experimental projects,which is helpful to improve students·scientific research literacy and practical ability.