A parallel variable neighborhood search algorithm with quadratic programming for cardinality constrained portfolio optimization

作者：

Highlights：

• The cardinality constrained portfolio optimization problem is considered.

• Variable neighborhood search is combined with quadratic programming.

• An asynchronous parallelization strategy is implemented.

• Several benchmark problems are solved, and the results are compared.

• Computational results confirm the competitiveness of the hybrid algorithm.

摘要

•The cardinality constrained portfolio optimization problem is considered.•Variable neighborhood search is combined with quadratic programming.•An asynchronous parallelization strategy is implemented.•Several benchmark problems are solved, and the results are compared.•Computational results confirm the competitiveness of the hybrid algorithm.

论文关键词：Metaheuristics,Variable neighborhood search,Asynchronous parallelization,Quadratic programming,Portfolio optimization

论文评审过程：Received 3 December 2019, Revised 16 April 2020, Accepted 18 April 2020, Available online 23 April 2020, Version of Record 25 April 2020.

论文官网地址：https://doi.org/10.1016/j.knosys.2020.105944