A stochastic linear fractional programming (SLFP) approach is developed for supporting
sustainable municipal solid waste management under uncertainty. The SLFP method can …

Waste management problems are subject to uncertainties presented as intervals, random
variables and/or fuzzy sets. During the past 20 years, inexact programming methods have …

This paper developed a multiobjective stochastic fractional goal programming (MOSFGP)
model for optimal water resources allocation among industries based on analyses of water …

In this study, a nonlinear fuzzy interval irrigation optimization model is developed for optimal
agricultural water allocation in Shijin irrigation district, Hebei province, China. The …

Waste management issues involve uncertainties represented as intervals, random variables,
and fuzzy sets related to intelligent processing. Over the last two decades, intelligent …

This paper developed a stochastic linear fractional programming model for industry
optimization allocation base on the uncertainty of water resources incorporating chance …

In this study a fuzzy chance constrained programming approach is developed for municipal
solid waste management to minimize the net system cost and maximize the revenue …

In this study, an inexact nonlinear programming model under uncertainty is developed by
incorporating a water production function into the crop irrigation system optimization …

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 …

In this study, an inexact inventory-theory-based chance-constrained programming (IICP)
model is proposed for planning waste management systems. The IICP model is derived …