AEGISi: Attribute Experimentation Guiding Improvement Searches Inline Framework
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.
Year of publication: |
2016
|
---|---|
Authors: | Racer, Michael ; Lovgren, Robin |
Published in: |
International Journal of Operations Research and Information Systems (IJORIS). - IGI Global, ISSN 1947-9336, ZDB-ID 2586955-3. - Vol. 7.2016, 2 (01.04.), p. 22-38
|
Publisher: |
IGI Global |
Subject: | AEGIS | Integer Programming Problem | Local Search Methods | Peripheral Information |
Saved in:
Online Resource
Saved in favorites
Similar items by person
-
AEGIS—attribute experimentation guiding improvement searches
Racer, Michael, (2009)
-
AEGIS : attribute experimentation guiding improvement searches ; offline framework
Racer, Michael, (2009)
-
Amini, Mehdi, (2012)
- More ...