Diversity-preserving quantum particle swarm optimization for the multidimensional knapsack problem

作者：

Highlights：

• The 0–1 multidimensional knapsack problem is a very popular combinatorial optimization problem.

• We design a quantum particle swarm algorithm with diversity preserving and effective local optimization.

• We show the competitiveness of the proposed algorithm compared to the state-of-the-art.

摘要

•The 0–1 multidimensional knapsack problem is a very popular combinatorial optimization problem.•We design a quantum particle swarm algorithm with diversity preserving and effective local optimization.•We show the competitiveness of the proposed algorithm compared to the state-of-the-art.

论文关键词：Binary optimization,Multidimensional knapsack problem,Population-based metaheuristics,Quantum particle swarm optimization,Diversity-preserving population updating strategy

论文评审过程：Received 28 August 2019, Revised 20 January 2020, Accepted 14 February 2020, Available online 22 February 2020, Version of Record 19 March 2020.

论文官网地址：https://doi.org/10.1016/j.eswa.2020.113310