Two-echelon location-routing optimization with time windows based on customer clustering

作者：

Highlights：

• A two-echelon location-routing problem is optimized based on customer partitioning.

• A mathematical model is proposed to minimize cost and maximize service reliability.

• Customers demand uncertainty is assumed and estimated during optimization.

• A modified NSGA-II method and a validity function are designed to obtain solutions.

• Computational results reveal that M-NSGA-II outperforms MOGA and MOPSO algorithms.

摘要

•A two-echelon location-routing problem is optimized based on customer partitioning.•A mathematical model is proposed to minimize cost and maximize service reliability.•Customers demand uncertainty is assumed and estimated during optimization.•A modified NSGA-II method and a validity function are designed to obtain solutions.•Computational results reveal that M-NSGA-II outperforms MOGA and MOPSO algorithms.

论文关键词：Location routing optimization with time windows,Periodic demand forecasting,Customer clustering,Validity measurement function,Non-dominated Sorting Genetic Algorithm-II (NSGA-II)

论文评审过程：Received 2 August 2017, Revised 12 February 2018, Accepted 11 March 2018, Available online 13 March 2018, Version of Record 3 April 2018.

论文官网地址：https://doi.org/10.1016/j.eswa.2018.03.018