A genetic algorithm-based matheuristic for hydrogen supply chain network problem with two transportation modes and replenishment cycles

被引：38

作者：

Woo, Young-Bin ^{[1
]}

Kim, Byung Soo ^{[1
]}

机构：

[1] Incheon Natl Univ, Dept Ind & Management Engn, 119 Acad Ro, Incheon 22012, South Korea

来源：

COMPUTERS & INDUSTRIAL ENGINEERING | 2019年 / 127卷

基金：

新加坡国家研究基金会;

关键词：

Hydrogen supply chain network; Matheuristic; Genetic algorithm; Mathematical programming; Replenishment cycle; REVERSE LOGISTICS NETWORK; MULTIOBJECTIVE OPTIMIZATION; STRATEGIC DESIGN; INFRASTRUCTURE; OPERATION; COST; BIOMASS; SAFETY;

D O I：

10.1016/j.cie.2018.11.027

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

This paper addresses a hydrogen supply chain network problem (HSCNP) with two transportation modes and replenishment cycles. For determining an optimal hydrogen supply chain network (HSCN), a mixed integer nonlinear programming (MINLP) model is developed. Due to the intractability caused by non-linear terms of the MINLP model, a genetic algorithm-based matheuristic (GAM) is proposed by including a mixed integer linear programming (MILP) combined within the procedure of genetic algorithm (GA). The performance of GAM is compared with two GAs by using randomly generated instances. Then, several sensitivity analyses of demand, transportation cost, and inventory carrying cost are conducted to evaluate an effect on a configuration of HSCN. Finally, optimal network configurations and selection of transportation modes are estimated under different future demand scenarios of Jeju Island, South Korea.

引用

页码：981 / 997

页数：17

共 44 条

[1] Design and operation of a future hydrogen supply chain - Snapshot model [J].