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A Multistage Evolutionary Algorithm for the Timetable Problem.

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Title: A Multistage Evolutionary Algorithm for the Timetable Problem.
Authors: Burke, E. K., Newall, J. P.
Source: IEEE Transactions on Evolutionary Computation. Apr1999, Vol. 3 Issue 1, p63. 12p. 4 Diagrams, 5 Charts, 8 Graphs.
Subjects: Algorithms, Genetic algorithms, Time perspective, Foundations of arithmetic
Abstract: It is well known that timetabling problems can be very difficult to solve, especially when dealing with particularly large instances. Finding near-optimal results can prove to be extremely difficult, even when using advanced search methods such as evolutionary algorithms (EA's). This paper presents a method of decomposing larger problems into smaller components, each of which is of a size that the EA can effectively handle. Various experimental results using this method show that not only can the execution time be considerably reduced but also that the presented method can actually improve the quality of the solutions. [ABSTRACT FROM AUTHOR]
Copyright of IEEE Transactions on Evolutionary Computation is the property of IEEE and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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DbLabel: Engineering Source
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PubType: Academic Journal
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  Data: A Multistage Evolutionary Algorithm for the Timetable Problem.
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  Data: <searchLink fieldCode="AR" term="%22Burke%2C+E%2E+K%2E%22">Burke, E. K.</searchLink><br /><searchLink fieldCode="AR" term="%22Newall%2C+J%2E+P%2E%22">Newall, J. P.</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Genetic+algorithms%22">Genetic algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Time+perspective%22">Time perspective</searchLink><br /><searchLink fieldCode="DE" term="%22Foundations+of+arithmetic%22">Foundations of arithmetic</searchLink>
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  Data: It is well known that timetabling problems can be very difficult to solve, especially when dealing with particularly large instances. Finding near-optimal results can prove to be extremely difficult, even when using advanced search methods such as evolutionary algorithms (EA's). This paper presents a method of decomposing larger problems into smaller components, each of which is of a size that the EA can effectively handle. Various experimental results using this method show that not only can the execution time be considerably reduced but also that the presented method can actually improve the quality of the solutions. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of IEEE Transactions on Evolutionary Computation is the property of IEEE and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1109/4235.752921
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      – SubjectFull: Genetic algorithms
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      – SubjectFull: Time perspective
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      – SubjectFull: Foundations of arithmetic
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      – TitleFull: A Multistage Evolutionary Algorithm for the Timetable Problem.
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              Text: Apr1999
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