An Improved DE Algorithm for Solving Multi-Furnace Optimal Scheduling of Single Crystal Silicon Production.

Autor: Kang, Lu, Liu, Ding, Wu, Yali, Ping, Guozheng
Předmět:
Zdroj: International Journal of Pattern Recognition & Artificial Intelligence; Feb2023, Vol. 37 Issue 2, p1-29, 29p
Abstrakt: Multi-furnace scheduling simultaneously is an important part to increase productivity and reduce the production cost in single crystal silicon enterprises. In the restrained power consumption requirements environment, the optimal sequencing of process operation start-time for single crystal furnaces is a challenging problem. To solve this problem, the scheduling model of multi-furnace scheduling is established in this paper to minimize the maximum completion time. Then, an improved DE algorithm called the multi-strategy individual adaptive mutation differential evolution algorithm (MSIADE) is presented to address the scheduling model. In the improved DE algorithm, the different dimensional and multi-strategy mutation operations are adopted to refrain the algorithm from the local optimal, then the different mutation factors are assigned to each individual through the rank of fitness function value to strengthen the exploration ability of the MSIADE algorithm. Simulation experiments results based on the standard test functions and the established scheduling model show the feasibility in the established model and the effectiveness in the proposed algorithm. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index