Complete code, data, annotation download link: Particle swarm algorithm-based course scheduling system, PSO-based course scheduling system resources - CSDN library https://download.csdn.net/download/abc991835105/88232566 Abstract Back view Improvement
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shubett
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Test ispso algorithm performance
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PSO class scheduling system optimization
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Summary
In view of the shortcomings of the basic particle swarm algorithm that is prone to premature convergence and falling into local optimality, an improved particle swarm algorithm based on Levy flight is proposed. In the particle position update formula, the late velocity term is prevented from having too little impact on the micro-convergence speed. The particle swarm is too busy flying and cannot jump out of the local optimum. Use Levy flight to change the position and movement direction of the particles to prevent them from falling into the local optimum. Select the optimal solution through a greedy update evaluation strategy to obtain the global optimum. Experimental results show that, compared with the basic particle swarm algorithm, the proposed improved particle swarm algorithm based on Levy flight can effectively improve the accuracy of the solution and speed up the convergence speed, and the optimization effect is better, and it can be applied to the class scheduling system.
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Teacher positions are subject to certain changes every year, and the number of classes changes. Classes need to be rescheduled every year. This article uses particle swarm algorithm to optimize class scheduling.
Test function shubert(ten)
The Shubert function is a periodic multimodal function. As shown in Figure 1, it has multiple global optimal values. As shown in Figure 2, there is only one global optimal value in a period and many local optimal solutions, which is suitable for testing the convergence of the algorithm. Performance, particle swarm algorithm is an algorithm with fast convergence speed and fast calculation speed. This article uses standard particle swarm algorithm to solve the problem. If you have any questions, please leave a message to communicate!
The function image is as follows