2020
DOI: 10.3390/su12051887
|View full text |Cite
|
Sign up to set email alerts
|

Optimizing the Raw Material Supply Chain of the Wood Biomass Power Generation Industry for Different Stakeholders’ Benefits: An Analysis of Inner Mongolia, China

Abstract: A large number of sand shrubs have been planted in western China, especially in Inner Mongolia. Sand shrubs produce a large amount of stump residue, and wood biomass power generation enterprises that use stump residue as raw materials have emerged in Wushen Banner and other areas. In this paper, the Mixed Integer Linear Programming (MILP) model is used to optimize the raw material supply chain of forest biomass power generation enterprises. Optimizations with different objectives represent the choices of diffe… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2022
2022
2024
2024

Publication Types

Select...
4

Relationship

0
4

Authors

Journals

citations
Cited by 4 publications
(1 citation statement)
references
References 18 publications
0
1
0
Order By: Relevance
“…Wang et al [5] developed a bi-objective mixed-integer nonlinear programming model to optimize the supply chain network consisting of raw material suppliers, final product manufacturers, and distribution centers. Bai et al [6] used the mixed-integer linear programming (MILP) model to optimize the raw material supply chain of forest biomass power generation enterprises. Razmi et al [7] developed a dynamic mixed-integer linear programming (DMILP) model to optimize a seasonal raw material supply chain network by considering a multilevel supply chain with multiple products and multiple time periods.…”
Section: Introductionmentioning
confidence: 99%
“…Wang et al [5] developed a bi-objective mixed-integer nonlinear programming model to optimize the supply chain network consisting of raw material suppliers, final product manufacturers, and distribution centers. Bai et al [6] used the mixed-integer linear programming (MILP) model to optimize the raw material supply chain of forest biomass power generation enterprises. Razmi et al [7] developed a dynamic mixed-integer linear programming (DMILP) model to optimize a seasonal raw material supply chain network by considering a multilevel supply chain with multiple products and multiple time periods.…”
Section: Introductionmentioning
confidence: 99%