Abstract
Abstract
In this study, a fuzzy-queue-based interval linear programming (FQ-ILP) model was first developed through introducing FQ model into an ILP framework. The FQ-ILP model can not only address system uncertainties with complex presentations, but also reflect the influence of FQ in decision-making problems. Moreover, it can be used for analyzing various policy scenarios that are associated with different waiting costs, fuzzy waiting times, and different operation costs. The method has been applied to a typical case study area for long-term municipal solid waste management planning. Interval solutions associated with fuzzy arrival rate, fuzzy service rate, and different waiting costs have been generated. They can be further used for generating decision alternatives and thus help waste managers to identify desired policies under various environmental, economic, and fuzzy queuing problems. Compared with the conventional optimization methods, the developed FQ-ILP model can more actually reflect the complexity of municipal solid waste management systems and provide more useful information for decision makers under uncertainty, resulting in increased system robustness. Results also suggest that the proposed method is applicable to other environment problems that involve uncertainties presented in multiple formats in the queuing models.