Development of Characterization and Optimization Methodologies for Waste Management

Abstract

Applications of mathematical models to waste management are usually complicated by the complexities involved in either waste treatment processes or waste management systems. In this dissertation research, a set of characterization and optimization methodologies have been developed and applied to waste management. In detail, they include: (a) a stepwise-cluster microbial biomass inference (SMI) model through introducing stepwise cluster analysis (SCA) into composting process modeling for tackling the nonlinear relationships between state variables and microbial activities; (b) a genetic algorithm (GA) aided stepwise cluster analysis (GASCA) method for describing the nonlinear relationships between the selected state variables and the C/N ratio in food waste composting; (c) an inexact piecewise quadratic programming (IPQP) model through coupling piecewise linear regression with interval-parameter quadratic programming for handling the nonlinear objective function in waste allocation planning; (d) an inexact piecewise-linearization-based fuzzy flexible programming (IPFP) model was developed to tackle nonlinear economies-of-scale (EOS) effects in intervalparameter constraints for a representative waste management problem; and (e) an inexact joint-probabilistic left-hand-side chance-constrained programming (IJLCP) method for reflecting the inexact relationships between amounts of waste transported and treated effectively. In terms of methodologies, the major contribution of this research includes: the SCA was for the first time, introduced into mapping the relationships in composting processes; the GASCA combining GA with SCA would possess abilities in both variable searching and nonlinear fitting; the IPQP and IPFP models were designed through introducing concepts of piecewise linearization to the related inexact programming methods; and a non-equivalent but sufficient linearization form for the IJLCP model was proposed and proved straightforwardly. In terms of applications, the major contribution involves: (a) based on the SCA and GASCA trees, the effects of the state variables on thermophilic bacteria, mesophilic bacteria, and the C/N ratio were quantified; (b) the applications of IPQP and IPFP implied that the often ignored EOS effects should be considered in the real-world waste management system to obtain accurate net system costs; and (c) the IJLCP’s application indicated that a higher joint probability level would result in a lower system costs in a waste management system.