Name
Abstract | ||
|---|---|---|
With the number of alternative systems increasing, the system portfolio selection problem for large-scale complex systems is an non-deterministic polynomial (NP)-hard problem. The time cost of the classification selection algorithm used for the portfolio selection is intolerable; thus, improving the algorithm is necessary. In this paper, first, the weapon system portfolio selection (WSPS) model is categorized into two types: single objective and multiobjective; the optimization difficulties are analyzed; and the feasible solution space reduction strategy is given. Second, a portfolio selection optimization algorithm based on the difference evolution technique for order preference by similarity to ideal solution (DE-TOPSIS) is proposed where the weapon system weighting method TOPSIS is integrated with the DE algorithm. Finally, considering different weapon system scales, the advantages of the proposed algorithm are illustrated by comparing it with two other algorithms in a single-target case and two other algorithms in a multiobjective case. The results indicate that the DE algorithm always has better performance with regard to optimal solution quality, convergence speed, and algorithm stability. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/JSYST.2019.2912409 | IEEE Systems Journal |
Keywords | Field | DocType |
Portfolios,Weapons,Optimization,Complex systems,Programming,Tools,Decision making | Complex system,Industrial engineering,Computer science,Computer network,Portfolio | Journal |
Volume | Issue | ISSN |
13 | 4 | 1932-8184 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yajie Dou | 1 | 5 | 5.88 |
| Danling Zhao | 2 | 2 | 2.07 |
| Boyuan Xia | 3 | 0 | 0.34 |
| Xiao-Xiong Zhang | 4 | 12 | 2.91 |
| kewei yang | 5 | 13 | 3.43 |