Planning of municipal solid waste management systems under mixed fuzzy and stochastic environment

Uncertainties are ubiquitous during the processes of waste generation, transportation, treatment and disposal, leading to complexities in municipal solid waste management. In order to address these uncertainties and complexities, an inexact fuzzy-stochastic programming approach based on superiority and inferiority measures is developed in this study for municipal solid waste management. This method could effectively tackle multiple uncertainties presented as interval values and possibilistic/probabilistic distributions. It overcomes the disadvantages of the interval-parameter linear programming where fuzzy boundaries of intervals are over-simplified into deterministic values; it also improves upon the superiority-inferiority-based fuzzy-stochastic programming approach by allowing interval numbers as modeling inputs. In addition, through introducing the concept of superiority and inferiority degrees, it would not lead to complicated intermediate models in its solution process as conventional methods do. Thus, it possesses lower computational requirements and higher feasibility. This method is then applied to a case study. The obtained results indicate that reasonable solutions have been generated. Moreover, a number of management alternatives could be generated through the results, which are more favoured by decision makers due to the increased flexibility and applicability. In general, the results from the case study demonstrate that this method is applicable to address various uncertainties that are inherent with real-world waste management problems.