Inexact fuzzy-stochastic quadratic programming approach for waste management under multiple uncertainties

In this study, an inexact fuzzy-stochastic quadratic programming (IFSQP) method is developed for effectively allocating waste to available facilities. The IFSQP approach is an extension of the conventional inexact linear programming for handling nonlinear programming in the objective function and multiple uncertainties on parameters in the constraints. The developed IFSQP is applied to a municipal solid waste management system. The objective is to minimize the total expected system cost by achieving optimal waste flow allocation over the entire planning horizon. The constraints include all of the relationships among decision variables, waste generation rates, waste diversion goals, and waste-management-facility capacities. The solutions of the IFSQP model can provide bases for selecting a desired waste management plan with reasonable cost and risk levels. The results indicate that reasonable solutions have been generated under different scenarios. The special characteristics of the proposed method make it unique compared with other optimization techniques that deal with uncertainties.