Portfolio decision analysis with a generalized balance approach

We consider a resource allocation problem in which the decision maker is responsible for selecting a group of projects to generate a portfolio, with the aim of maximizing the total benefit, and distributing the budget in a balanced way across different categories. We assume that the decision maker defines an interval for the desired share of each category. We propose augmented epsilon-constraint method to generate the nondominated solutions considering two objective functions: total benefit and balance among categories. The solution time increases with the problem size, and augmented epsilon-constraint method fails to find all nondominated solutions. We therefore develop a variable neighborhood search algorithm for the purpose of generating the nondominated frontier. Our computational experiments show that the nondominated frontier can be accurately estimated with respect to different performance measures.

Automated summary

This article focuses on a resource allocation problem, where the decision maker needs to select a group of projects to create a portfolio that maximizes the total benefit while balancing the budget across different categories. The augmented epsilon-constraint method and variable neighborhood search algorithm are proposed to find the nondominated solutions and estimate the nondominated frontier accurately, respectively. Computational experiments are conducted to validate the proposed methods.