郭海湘 Period sewage recycling vehicle routing problem based on real-time data

我校经济管理学院郭海湘老师在T2级别期刊——《Journal of Cleaner Production》上发表题为“Period sewage recycling vehicle routing problem based on real-time data”。论文第一作者郭海湘为经济管理学院教授，博士生导师

Abstract /摘要：

The period vehicle routing problem (PVRP) is an important extension of the vehicle routing problem, in which customers have a certain frequency of service. This paper studies a real-time period vehicle routing system: Daniudi gas field sewage recycling, which differs from the classic PVRP because the frequency of customer service is uncertain. A "prediction + two-stage" strategy is proposed to solve the problem. First, the integrated model predicts customers' sewage data generated that day to calculate the warning line so that customers who reach the warning line can be served on that day. Then, because the customer's sewage production changes in real time, a two-stage “pre-optimization + real-time optimization” model is proposed for each day in the period. The two-stage “pre-optimization + real-time optimization” model uses differential evolution (DE) algorithm based on niche clearing to plan the sewage recycling route. The computational results indicate that the proposed technique can reduce actual sewage recycling costs by 17.3%. By performing comparison experiments, we find that the five algorithms examined (i.e., jDE-niche, jDE, DE, GA, and ACO) reduce costs by 17.3%, 12.00%, 10.70%, 9.02% and 8.18%, respectively. Furthermore, the fifteen combined prediction models confirm the validity and effectiveness of our proposed "prediction+two-stage" strategy and jDE-niche algorithm.

论文信息;

Title/题目:

Period sewage recycling vehicle routing problem based on real-time data

Authors/作者:

Haixiang Guo;Fang Wan;Wenwen Pan;Mingyun Gu

Key Words /关键词：

real-time data;integrated prediction model;improved DE algorithm;period vehicle routing problem;sewage recycling

Indexed by /核心评价：

EI;Scopus;SCI;WAJCI;INSPEC;AHCI;

研究要点/ Highlights

Studied a real-time period vehicle routing system: Daniudi Gas Field sewage recycling.;Proposed a "prediction+two-stage" strategy to solve the sewage recycling problem.;Integrated four prediction models to predict sewage streaming data.;Presented an improved DE algorithm to plan sewage recycling routes.;Demonstrated the effectiveness of our algorithm and model by performing extensive experiments.

DOI：10.1016/J.JCLEPRO.2020.125628

全文链接：https://www.sciencedirect.com/science/article/pii/S0959652620356742