Inexact rough-interval type-2 fuzzy stochastic optimization model supporting municipal solid waste management under uncertainty

ABSTRACT

In this study, an inexact rough-interval type-2 fuzzy stochastic linear programming (IRIT2FSLP) approach is developed for addressing uncertainties presented as rough-interval, type-2 fuzzy and random variables. The proposed method is applied to the case of a long-term municipal solid waste management system. The IRIT2FSLP approach is an extension of the inexact interval linear programming for handling nonlinear stochastic optimization problems where rough-interval and type-2 fuzzy parameters are integrated into a general framework. The results indicate that IRIT2FSLP normally leads to rough-interval solutions. Comparisons of the proposed model with scenarios without rough-interval and type-2 fuzzy parameters are also conducted. The results indicate the significant impact of dual-uncertain information on the system, which implies the reliability of IRIT2FSLP in handling waste flow allocation.

KEYWORDS:

• Rough-interval
• type-2 fuzzy
• stochastic
• linear programming
• uncertainty

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This research was supported by the Fujian Education Research Project for Young and Middle-aged Teachers of Education Department [grant number JAT170424]; Natural Science Foundation of Fujian Province [grant number 2018J01527].