Yang, Qing-YongChu, Shu-ChuanChen, Chien-MingPan, Jeng-ShyangHow to solve the Job-Shop Scheduling problem (JSP) effectively and make the most efficient use of resources has always been the focus of academic and engineering circles. Aiming at the traditional JSP problem, this paper proposes a new QUasi-Affine Transformation Evolution algorithm (QUATRE) to solve it, called QUATRE-SAO for short. The QUATRE-SAO algorithm combines Simulated Annealing (SA) strategy and Opposition-based Learning (OBL) strategy to enhance the algorithm to jump out of local optimum and further improve the optimization performance of the algorithm. Through the comparative experiment of FT and LA series standard test examples, the results show that the QUATRE-SAO algorithm can solve the JSP problem better and can get a better solution.
An QUasi-Affine TRansformation Evolution (QUATRE) Algorithm for Job-Shop Scheduling Problem by Mixing Different Strategies
Smart Innovation, Systems and Technologies
Advances in Smart Vehicular Technology, Transportation, Communication and Applications ; Kapitel : 16 ; 167-175
2021-11-30
9 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
QUasi-Affine TRansformation Evolutionary Algorithm for Feature Selection
Springer Verlag | 2021
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