A portfolio selection model based on the knapsack problem under uncertainty

PLoS One. 2019 May 1;14(5):e0213652. doi: 10.1371/journal.pone.0213652. eCollection 2019.


One of the primary concerns in investment planning is to determine the number of shares for asset with relatively high net value of share such as Berkshire Hathaway on Stock market. Traditional asset allocation methods like Markowitz theorem gives the solution as a percentage and this ratio may suggest allocation of half of a share on the market, which is impractical. Thus, it is necessary to propose a method to determine the number of shares for each asset. This paper presents a knapsack based portfolio selection model where the expected returns, prices, and budget are characterized by interval values. The study determines the priority and importance of each share in the proposed model by extracting the interval weights from an interval comparison matrix. The resulted model is converted into a parametric linear programming model in which the decision maker is able to determine the optimism threshold. Finally, a discrete firefly algorithm is designed to find the near optional solutions in large dimensions. The proposed study is implemented for some data from the US stock exchange.

MeSH terms

  • Algorithms
  • Investments*
  • Programming, Linear
  • Uncertainty*

Grants and funding

The authors received no specific funding for this work.