Design for sustainability of industrial symbiosis based on emergy and multi-objective particle swarm optimization

Jingzheng Ren; Hanwei Liang; Liang Dong; Lu Sun; Zhiqiu Gao

doi:10.1016/j.scitotenv.2016.04.092

Design for sustainability of industrial symbiosis based on emergy and multi-objective particle swarm optimization

Sci Total Environ. 2016 Aug 15:562:789-801. doi: 10.1016/j.scitotenv.2016.04.092. Epub 2016 Apr 22.

Authors

Jingzheng Ren¹, Hanwei Liang², Liang Dong³, Lu Sun⁴, Zhiqiu Gao⁵

Affiliations

¹ Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disaster, School of Geography and Remote Sensing, Nanjing University of Information Science & Technology, Nanjing 210044, China; Centre for Engineering Operations Management, Department of Technology and Innovation, University of Southern Denmark, Campusvej 55, 5230 Odense M, Denmark. Electronic address: renjingzheng123321@163.com.
² Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disaster, School of Geography and Remote Sensing, Nanjing University of Information Science & Technology, Nanjing 210044, China.
³ Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disaster, School of Geography and Remote Sensing, Nanjing University of Information Science & Technology, Nanjing 210044, China; CML, Leiden University, Leiden, The Netherlands; Center for Social and Environmental Systems Research, National Institute for Environmental Studies (NIES), Onogawa 16-2, Tsukuba-City, Ibaraki 305-8506, Japan.
⁴ Center for Social and Environmental Systems Research, National Institute for Environmental Studies (NIES), Onogawa 16-2, Tsukuba-City, Ibaraki 305-8506, Japan; Department of Environment Systems, Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa-shi, Chiba 277-8563, Japan.
⁵ State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China. Electronic address: zgao@mail.iap.ac.cn.

PMID: 27110990
DOI: 10.1016/j.scitotenv.2016.04.092

Abstract

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.

Keywords: Chemical complex; Design for sustainability; Emergy; Industrial symbiosis; Particle Swarm Algorithm.

Publication types

Research Support, Non-U.S. Gov't