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Content Provider | IEEE Xplore Digital Library |
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Author | Zhao Man Tan Wei Li Xiang Kang Lishan |
Copyright Year | 2008 |
Description | Author affiliation: Sch. of Comput., China Univ. of Geosci., Wuhan (Zhao Man; Tan Wei; Li Xiang; Kang Lishan) |
Abstract | A simulated annealing genetic algorithm was put forward to solve the resource-constrained multi-project scheduling problem. The ordinary genetic algorithm and simulated annealing algorithm used in this method were improved separately firstly. Then the simulated annealing operations which can overcome the defects of genetic algorithm easy to fall into the local optimal solution were used in the genetic algorithm. The method also inherited the rapid convergence characteristic of genetic algorithm. It was proved by a practical example that this hybrid algorithm improved the deficiencies of genetic algorithm and simulated annealing and can effectively shorten the implementation time of projects. Compared with other heuristic and intelligent methods, this algorithm performs better than them. |
Starting Page | 390 |
Ending Page | 394 |
File Size | 273648 |
Page Count | 5 |
File Format | |
ISBN | 9780769533360 |
DOI | 10.1109/CSSE.2008.925 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2008-12-12 |
Publisher Place | China |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Multi-project scheduling simulated annealing Computational modeling Geology Laboratories resource constraint heuristic methods Genetic algorithms Computer science Constraint optimization genetic algorithm Processor scheduling Simulated annealing Resource management Software engineering |
Content Type | Text |
Resource Type | Article |
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