Robustness in optimal design of Eco-Industrial Parks under the lens of two-stage stochastic optimization

IF 3.9 2区 工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Computers & Chemical Engineering Pub Date : 2023-09-09 DOI:10.1016/j.compchemeng.2023.108399
Gianfranco Liberona , Alessandro Di Pretoro , Stéphane Negny , Ludovic Montastruc , David Salas
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引用次数: 1

Abstract

An eco-industrial park (EIP) is a community of businesses located together on a common property, that seek to reduce environmental and economical impact of their operation by collaborating and sharing materials and wastes. In practice, operations within an EIP have daily variations, and therefore are constantly facing uncertainty. In this work, a methodology to design efficient EIPs that are also robust to daily (uncertain) variations of the nominal operation of the enterprises is proposed. The attention is mainly focused in water exchange networks. Probability functions are used to measure robustness and propose a Sample Average Approximation technique to solve the associated optimization problem. Simulations based on literature examples are performed to illustrate the approach.

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两阶段随机优化视角下生态工业园区优化设计的稳健性
生态工业园区(EIP)是一个位于共同财产上的企业社区,旨在通过合作和共享材料和废物来减少其运营对环境和经济的影响。在实践中,EIP内的操作每天都有变化,因此经常面临不确定性。在这项工作中,提出了一种设计高效eip的方法,该方法对企业名义运营的日常(不确定)变化也具有鲁棒性。注意力主要集中在水交换网络上。使用概率函数来衡量鲁棒性,并提出了一种样本平均逼近技术来解决相关的优化问题。基于文献实例的仿真验证了该方法。
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来源期刊
Computers & Chemical Engineering
Computers & Chemical Engineering 工程技术-工程:化工
CiteScore
8.70
自引率
14.00%
发文量
374
审稿时长
70 days
期刊介绍: Computers & Chemical Engineering is primarily a journal of record for new developments in the application of computing and systems technology to chemical engineering problems.
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