Title :
Resource-constrained multi-project scheduling based on ant colony neural network
Author :
Xue, Hong-quan ; Wei, Sheng-min ; Wang, Yang-en
Author_Institution :
Sch. of Mech. Eng., Northwestern Polytech. Univ., Xi´´an, China
Abstract :
The resource-constrained multi-project scheduling (RCMPS) is a NP-hard problem and has been extensively used in manufacturing and engineering fields. In order to solve scheduling of RCMPS, a new algorithm was presented in this paper. The new algorithm combines the some advantages of ACOA and NN . Finally, the algorithm was tested on a case of the RCMPS and the results were presented in the paper. The experimental results show that the new algorithm effectively relieves the disadvantages of ACOA and NN in RCMPS.
Keywords :
computational complexity; constraint handling; neural nets; optimisation; project management; scheduling; NP-hard problem; ant colony neural network; resource constrained multiproject scheduling; Algorithm design and analysis; Artificial neural networks; Heuristic algorithms; Job shop scheduling; NP-hard problem; Optimization; Resource-constrained multi-project scheduling; ant colony neural network; ant colony optimization; neural network;
Conference_Titel :
Apperceiving Computing and Intelligence Analysis (ICACIA), 2010 International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-8025-8
DOI :
10.1109/ICACIA.2010.5709877
