
Research Article
Applying Design of Experiments to Evaluate the Influence of Parameters on the Economic Feasibility of the Eco-Industrial Parks
@INPROCEEDINGS{10.1007/978-3-031-59462-5_11, author={Kien Cao-Van}, title={Applying Design of Experiments to Evaluate the Influence of Parameters on the Economic Feasibility of the Eco-Industrial Parks}, proceedings={Nature of Computation and Communication. 9th EAI International Conference, ICTCC 2023, Ho Chi Minh City, Vietnam, October 26-27, 2023, Proceedings}, proceedings_a={ICTCC}, year={2024}, month={5}, keywords={Eco-industrial park Design of experiments Single-leader multi-follower game Logistic regression Multi-linear regression}, doi={10.1007/978-3-031-59462-5_11} }
- Kien Cao-Van
Year: 2024
Applying Design of Experiments to Evaluate the Influence of Parameters on the Economic Feasibility of the Eco-Industrial Parks
ICTCC
Springer
DOI: 10.1007/978-3-031-59462-5_11
Abstract
This research employs the design of experimental (DoE) to examine how various parameters impact the economic feasibility and overall satisfaction of enterprises operating within eco-industrial parks (EIPs). A full factorial design is constructed, using economic feasibility and overall satisfaction as response variables, and experimental data is generated by simulating diverse scenarios. Each iteration of the experiment utilizes a single-leader multi-follower (SLMF) game optimization model, focusing on designing water exchange networks within EIPs. The investigation encompasses several parameters in a case study involving ten follower enterprises aiming to minimize their annual operational costs. Concurrently, the EIP authority assumes the leader role with the objective of reducing the collective freshwater consumption of the EIP. Furthermore, this study employs binary logistic and multi-linear regressions to establish causal relationships. These relationships link input parameters with economic feasibility and overall satisfaction of operating businesses within EIPs. Ultimately, the reliability of the DoE methodology is showcased, offering valuable insights into enterprise parameters, EIP design, economic feasibility, and overall satisfaction.