Bilevel fuzzy optimization model of an algae-based eco-industrial park under cooperative game theory

• Main Author: Aguilar, Kyle Darryl T.
• Format: text
• Language: English
• Published: Animo Repository 2017
• Subjects: Industrial districts > Philippines; Environmental protection > Case studies
• Online Access: https://animorepository.dlsu.edu.ph/etd_masteral/5377
• Institution: De La Salle University

The successful transition from fossil fuels to algal biofuels could contribute in addressing the pressing environmental problems of every nation. To ensure the effectiveness of the proposed solution, the use of eco-industrial parks or EIPS was proposed to improve the sustainability of algal biofuels. EIPs operated on industrial symbiosis wherein economic and environmental benefits were achieved through a collaborative exchange of resources among member plants. The development of EIPs was driven by a body of higher authority or a leader such as the government to facilitate and influence its operation. The EIP was composed of member industrial plants or followers. Given the conflicting nature of the objectives of the stakeholders, the leader could indirectly influence the followers into achieving the formers objective through control variables such as incentives. EIP optimization studies incorporating the interaction between the leader and the followers had not yet considered the rational decision-making behavior of the stakeholders. The paretooptimal solution for the EIP design might not be acceptable for the decision-makers involved. Thus, the current study developed a bilevel fuzzy optimization model of an algae-based EIP under a cooperative theory-based benefit allocation framework. The proposed bilevel model first involved the determination of the optimal compromise solution between the leaders and followers. The net economic benefit of the EIP was then distributed among the followers commensurate to their marginal contribution in improving the feasibility of the EIP. In addition, a comparative optimal configuration generation framework was proposed that provided the stakeholders with the range of validated design solutions when the EIP was under full leader control, under full follower control, under the bilevel system, and under the cooperative theory-based benefit allocation framework. The proposed framework enabled the visualization of the advantages and trade-offs for each pareto-optimal solution generated through the pareto frontier. The results of the study signified the feasibility of a compromise EIP design solution between the leaders and followers with a degree of satisfaction of 0.78. Furthermore, the advantages and tradeoffs of allocating economic benefits among the industrial plants through cooperative game theory was compared with those of the conventional bilevel fuzzy optimization model. In addition, the comparative optimal configuration generation framework validated the obtained results and generated the range of possible pareto-optimal and feasible solutions for various EIP control conditions. The proposed model and framework could serve as a supplementary decision-making tool for the stakeholders given its capacity to provide a series of validated design solutions paired with a visual representation of the corresponding advantages and trade-offs of each.