Volume 8, Issue Supplement 2, December 2015, Pages 41 - 53
Portfolio Optimization From a Set of Preference Ordered Projects Using an Ant Colony Based Multi-objective Approach
Authors
S. Samantha Bastiani, Laura Cruz-Reyes, Eduardo Fernandez, Claudia Gomez
Corresponding Author
S. Samantha Bastiani
Received 29 July 2015, Accepted 30 October 2015, Available Online 1 December 2015.
- DOI
- 10.1080/18756891.2015.1129590How to use a DOI?
- Keywords
- Project portfolio, multi-objective optimization, ant-colony meta-heuristic, Multi-Criteria Decision
- Abstract
In this paper, a good portfolio is found through an ant colony algorithm (including a local search) that approximates the Pareto front regarding some kind of project categorization, cardinalities, discrepancies with priorities given by the ranking, and the average rank of supported projects; this approach is an improvement towards a proper modeling of preferences. The available information is only projects’ ranking and costs, and usually, resource allocation follows the ranking priorities until they are depleted. Results show that our proposal outperforms previous approaches.
- Copyright
- © 2017, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - JOUR AU - S. Samantha Bastiani AU - Laura Cruz-Reyes AU - Eduardo Fernandez AU - Claudia Gomez PY - 2015 DA - 2015/12/01 TI - Portfolio Optimization From a Set of Preference Ordered Projects Using an Ant Colony Based Multi-objective Approach JO - International Journal of Computational Intelligence Systems SP - 41 EP - 53 VL - 8 IS - Supplement 2 SN - 1875-6883 UR - https://doi.org/10.1080/18756891.2015.1129590 DO - 10.1080/18756891.2015.1129590 ID - Bastiani2015 ER -