Please use this identifier to cite or link to this item:
Title: Using constraint satisfaction adaptive neural network and efficient heuristics for job-shop scheduling
Authors: Yang, S
Wang, D
Keywords: Constraint satisfaction adaptive neural network;Heuristics;Job-shop scheduling;Integer linear programming
Issue Date: 1999
Citation: Information and Control, 28(2), 121 - 126, April 1999
Abstract: This paper proposes a new adaptive neural network , based on constraint satisfaction, and efficient heuristics hybrid algorithm for job-shop scheduling. The neural network has the property of adapting its connection weights and biases of neural units while solving feasible solution. Heuristics are used to improve he property of neural network and to obtain local optimal solution from solved feasible solution by neural network with orders of operations determined and unchanged. Computer simulations have shown that the proposed hybrid algorithm is of high speed and excellent efficiency.
Appears in Collections:Computer Science
Dept of Computer Science Research Papers

Files in This Item:
File Description SizeFormat 
Fulltext Chinese.pdf461.34 kBAdobe PDFView/Open

Items in BURA are protected by copyright, with all rights reserved, unless otherwise indicated.