Abstract

Industrial symbiosis (IS), which is a concept that allows enterprises to reduce material consumption and production cost, is widely used to optimize eco-industrial parks (EIPs). However, the IS formed in different regions and industrial fields may have different performances in terms of environmental, economic, and social aspects, and few studies are focusing on the IS optimization of material exchange relationships in EIPs in desert areas. Therefore, a multi-objective mixed-integer linear programming (MILP) model is proposed in the present study to optimize the environmental, economic, and social objectives of IS in Ulan Buh Demonstration Eco-industrial Park (UBD-EIP). Then the model is solved using the augmented ε-constraint method and 20 efficient solutions are obtained. The results show that the construction of IS can reduce the environmental impact by 50.24%–50.79%, decrease the operating costs by 42.95%–43.57%, and create a considerable number of job opportunities. The trade-off between environmental and economic objectives suggests that an increase in priority for economic objectives results in higher levels of raw material consumption and waste emissions. The proposed model can help decision-makers of EIPs to choose appropriate material exchange relationships according to objective priority choices. This article enriches the types of objective functions for multi-objective optimizations and provides a reference for IS optimization and sustainable development of industries in desert areas and mixed agricultural-industrial systems.

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