网络化工物流:效率-价值-环境 功能化的共生算法和应用
Yizheng Lyu1, Zhuoer Andrew Feng2, Tianshu Ji3
1School of Environment, Tsinghua University, Beijing 100084, China.
Environmental science & technology
|November 7, 2023
概括
本研究引入了两种新的算法,以优化化学工业集群,确定促进经济效益和减少可持续化学制造对环境的影响的共生关系.
科学领域:
- 化学工程是化学工程的重要组成部分.
- 工业生态学 工业生态学
- 运营研究 运营研究
背景情况:
- 化学工业集群 (CICs) 提供了通过共生来优化资源和减少废物的机会.
- 实现化学工业的可持续性需要最大限度地提高经济效益并最大限度地减少对环境的影响.
- 目前的CIC可能无法充分利用潜在的共生关系以提高效率.
研究的目的:
- 为化学工业集群设计和验证创新的共生算法.
- 量化实施优化共生关系的经济和环境效益.
- 在CIC中为污染和碳减排战略提供理论支持.
主要方法:
- 开发CIC的最长路径算法和最大共生算法.
- 将算法应用于具有569种原材料和435种产品的原型CIC.
- 分析化学特征,流动模式和集群内的现有关系.
主要成果:
- 最长路径算法确定了一个5家企业的染料产业链.
- 最大共生算法揭示了218个共生对,增加了910万的化学物质.
- 共生关系带来了12.5亿元人民币的成本节约和0.62-11.87倍的生命周期效益.
结论:
- 开发的算法有效地优化CIC,以提高经济和环境绩效.
- 实施共生算法有助于实现化学工业的可持续性目标.
- 这种跨学科的方法为工业集群中的污染和碳减排提供了基础.
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