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AEGISi: Attribute Experimentation Guiding Improvement Searches Inline Framework

AEGISi: Attribute Experimentation Guiding Improvement Searches Inline Framework

Michael Racer, Robin Lovgren
Copyright: © 2016 |Volume: 7 |Issue: 2 |Pages: 17
ISSN: 1947-9328|EISSN: 1947-9336|EISBN13: 9781466691292|DOI: 10.4018/IJORIS.2016040102
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MLA

Racer, Michael, and Robin Lovgren. "AEGISi: Attribute Experimentation Guiding Improvement Searches Inline Framework." IJORIS vol.7, no.2 2016: pp.22-38. http://doi.org/10.4018/IJORIS.2016040102

APA

Racer, M. & Lovgren, R. (2016). AEGISi: Attribute Experimentation Guiding Improvement Searches Inline Framework. International Journal of Operations Research and Information Systems (IJORIS), 7(2), 22-38. http://doi.org/10.4018/IJORIS.2016040102

Chicago

Racer, Michael, and Robin Lovgren. "AEGISi: Attribute Experimentation Guiding Improvement Searches Inline Framework," International Journal of Operations Research and Information Systems (IJORIS) 7, no.2: 22-38. http://doi.org/10.4018/IJORIS.2016040102

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Abstract

The quality of a solution to an integer programming problem is a function of a number of elements. Lightly constrained problems are easier to solve than those with tighter constraints. Local search methods generally perform better than greedy methods. In the companion paper to this one, the authors investigated how peripheral information could be gathered and utilized to improve solving subsequent problems of the same type. In the current paper, they extend this to the dynamic environment – that is, utilizing such “peripheral” information as the solver is in progress, in order to determine how best to proceed.

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