TY - JOUR
T1 - Design for sustainability of industrial symbiosis based on emergy and multi-objective particle swarm optimization
AU - Ren, Jingzheng
AU - Liang, Hanwei
AU - Dong, Liang
AU - Sun, Lu
AU - Gao, Zhiqiu
N1 - Publisher Copyright:
© 2016 Elsevier B.V..
PY - 2016/8/15
Y1 - 2016/8/15
N2 - Industrial symbiosis provides novel and practical pathway to the design for the sustainability. Decision support tool for its verification is necessary for practitioners and policy makers, while to date, quantitative research is limited. The objective of this work is to present an innovative approach for supporting decision-making in the design for the sustainability with the implementation of industrial symbiosis in chemical complex. Through incorporating the emergy theory, the model is formulated as a multi-objective approach that can optimize both the economic benefit and sustainable performance of the integrated industrial system. A set of emergy based evaluation index are designed. Multi-objective Particle Swarm Algorithm is proposed to solve the model, and the decision-makers are allowed to choose the suitable solutions form the Pareto solutions. An illustrative case has been studied by the proposed method, a few of compromises between high profitability and high sustainability can be obtained for the decision-makers/stakeholders to make decision.
AB - Industrial symbiosis provides novel and practical pathway to the design for the sustainability. Decision support tool for its verification is necessary for practitioners and policy makers, while to date, quantitative research is limited. The objective of this work is to present an innovative approach for supporting decision-making in the design for the sustainability with the implementation of industrial symbiosis in chemical complex. Through incorporating the emergy theory, the model is formulated as a multi-objective approach that can optimize both the economic benefit and sustainable performance of the integrated industrial system. A set of emergy based evaluation index are designed. Multi-objective Particle Swarm Algorithm is proposed to solve the model, and the decision-makers are allowed to choose the suitable solutions form the Pareto solutions. An illustrative case has been studied by the proposed method, a few of compromises between high profitability and high sustainability can be obtained for the decision-makers/stakeholders to make decision.
KW - Chemical complex
KW - Design for sustainability
KW - Emergy
KW - Industrial symbiosis
KW - Particle swarm algorithm
UR - https://www.scopus.com/pages/publications/84963948611
U2 - 10.1016/j.scitotenv.2016.04.092
DO - 10.1016/j.scitotenv.2016.04.092
M3 - 文章
AN - SCOPUS:84963948611
SN - 0048-9697
VL - 562
SP - 789
EP - 801
JO - Science of the Total Environment
JF - Science of the Total Environment
ER -