A hybrid particle swarm optimization algorithm for satisficing data envelopment analysis under fuzzy chance constraints

作者：

Highlights：

• A new satisficing DEA model with credibility criterion is presented in this paper.

• The sensitivity analysis of the proposed model is conducted, and some useful results are obtained.

• A hybrid PSO algorithm is designed to solve the proposed DEA model.

• Some comparison study via numerical experiments are performed.

• The designed hybrid PSO algorithm outperforms the hybrid GA in terms of runtime and solution quality.

摘要

•A new satisficing DEA model with credibility criterion is presented in this paper.•The sensitivity analysis of the proposed model is conducted, and some useful results are obtained.•A hybrid PSO algorithm is designed to solve the proposed DEA model.•Some comparison study via numerical experiments are performed.•The designed hybrid PSO algorithm outperforms the hybrid GA in terms of runtime and solution quality.

论文关键词：Data envelopment analysis,Credibility criterion,Approximation method,Neural network,Particle swarm optimization

论文评审过程：Available online 13 September 2013.

论文官网地址：https://doi.org/10.1016/j.eswa.2013.09.007