Portfolio Optimization From a Set of Preference Ordered Projects Using an Ant Colony Based Multi-objective Approach

被引：0
|
作者：
S. Samantha Bastiani
Laura Cruz-Reyes
Eduardo Fernandez
Claudia Gomez
机构：
[1] Tijuana Institute of Technology,National Mexican Institute of Technology
[2] National Mexican Technology/Madero Institute of Technology,Postgraduate & Research Division
[3] Autonomous University of Sinaloa,Faculty of Civil Engineering
[4] National Mexican Technology/Madero Institute of Technology,Postgraduate & Research Division
来源：
International Journal of Computational Intelligence Systems | 2015年 / 8卷
关键词：
Project portfolio; multi-objective optimization; ant-colony meta-heuristic; Multi-Criteria Decision;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
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.
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页码：41 / 53
页数：12
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