In real-life problems, while the available information is often inadequate and the distribution functions are often unknown, it is generally possible to represent the obtained data with inexact numbers that can be readily used in the inexact programming models. A major advantage of inexact programming is that the variation in system performance and decision variables can be investigated by solving relatively simple sub-models. The approach of operational programming with inexact analysis often treats the uncertain parameters as intervals with known lower and upper bounds and unclear distributions. In some of the works such as, the nonlinear objective functions are converted into linear functions or simplified into quadratic functions under some adopted conditions and assumptions. Due to complexity of the problem, research reports on nonlinear programming problems for solid waste management are scarce some exceptions are. The techniques employed include linear programming, mixed integer linear programming, multi-objective programming, nonlinear programming, as well as their hybrids, which involve probability, fuzzy set and inexact analysis. The primary considerations involved are cost control, environmental sustainability and waste reutilization. Different models of waste planning have been researched and applied in various engineering fields in the following decades. Economic optimization in the operation programming of solid waste management was first proposed in the 1960s.
Municipal solid waste management involves activities such as waste collection, transportation, treatment, reutilization, and disposal.
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