Modeling and multi-objective optimization of multi-period biofuel supply chain

LIU Zhexuan; QIU Tong; CHEN Bingzhen

doi:10.3969/j.issn.0438-1157.2014.07.042

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Modeling and multi-objective optimization of multi-period biofuel supply chain

更新时间：2025-12-10

- Modeling and multi-objective optimization of multi-period biofuel supply chain
- CIESC Journal Issue 7, Pages: 2802-2812(2014)
- 作者机构：
  
  清华大学化学工程系,北京,100084
- 作者简介：
- 基金信息：
- DOI：10.3969/j.issn.0438-1157.2014.07.042
  CLC： Q021.8
- Online First：05 July 2014，
  
  Published：05 July 2014
- 稿件说明：
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LIU Zhexuan, QIU Tong, CHEN Bingzhen. Modeling and multi-objective optimization of multi-period biofuel supply chain[J]. CIESC Journal, 2014, (7): 2802-2812.
DOI：

LIU Zhexuan, QIU Tong, CHEN Bingzhen. Modeling and multi-objective optimization of multi-period biofuel supply chain[J]. CIESC Journal, 2014, (7): 2802-2812. DOI： 10.3969/j.issn.0438-1157.2014.07.042.

摘要

建立了一个基于多目标优化以及生命周期评价（LCA）的多期生物燃料供应链模型。该模型的3个目标函数分别为总折现利润、平均单位能量生物燃料的温室气体排放和化石能源投入（economic，energy，environmental，3E）。为了将生物质生产的季节性以及库存等问题引入模型中，需要对每年进行多期划分。考虑到需要进一步引入供应链的扩张，模型的时间跨度设定为3年。此外，该模型还考虑了生物质产地、工厂，生物燃料市场的选址以及各节点间的物流流量等问题。通过将非线性的后两个目标函数利用ε-constraint法转化为线性约束条件，该模型最终被转化为混合整数线性规划（MILP）问题并得以求解。对解得的非劣解在三维坐标系上线性插值可得非劣解所在曲面，它揭示了3E目标之间的权衡取舍关系。还使用了一个基于中国国情的数据的案例对该模型进行检验。

Abstract

This paper presents a life cycle assessment (LCA) based multi-period and multi-objective biofuel supply chain model. The objective functions are total discounted profit

average fossil energy input per MJ biofuel and average greenhouse gases emission per MJ biofuel (economic

energy

environmental

3E). Considering seasonal factor and storage problem

a multi-period model was required. Furthermore

to investigate the expansion of the supply chain

the time span of the model was set to be 3 years. The locations of biomass feedstock

biofuel factories and markets were considered as decision variables in the model. The non-linear objective functions were transformed into linear constraints by using the ε-constraint method. After that

the model was solved as a MILP problem. A surface of the Pareto optimal solutions was obtained by linearly interpolating the non-inferior solutions. The surface revealed the tradeoff among 3E objectives. In the case study

this model was used to design an experimental biofuel supply chain for China.

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