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Content Provider | IEEE Xplore Digital Library |
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Author | Shen, C.-Y. Pao, Y.-H. Yip, P. |
Copyright Year | 1994 |
Description | Author affiliation: Dept. of Electr. Eng. & Appl. Phys., Case Western Reserve Univ., Cleveland, OH, USA (Shen, C.-Y.; Pao, Y.-H.; Yip, P.) |
Abstract | This paper reports on an investigation of whether a special type of evolutionary programming named guided evolutionary simulated annealing (GESA) might be used effectively for dealing with scheduling tasks. The GESA approach allows many candidate solutions to be 'alive' at the same time. There is local competition and global competition and more and more search resources are guided into promising regions. Simulated annealing avoids entrapment in local minima. Two examples of multiple job scheduling were investigated. Results obtained with GESA were superior to those obtained with a simulated annealing approach described in prior literatures.< |
Starting Page | 702 |
Ending Page | 706 |
File Size | 336629 |
Page Count | 5 |
File Format | |
ISBN | 0780318994 |
DOI | 10.1109/ICEC.1994.349972 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 1994-06-27 |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Simulated annealing Optimal scheduling Job shop scheduling Scheduling algorithm Stochastic processes Physics Genetic programming Timing NP-complete problem Iterative algorithms |
Content Type | Text |
Resource Type | Article |
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