Research On Municipal Solid Waste Management Systems Under Uncertainty

In the past decades, uncertainties and complexities in municipal solid waste management system planning have been a critical concern. Effective management for municipal solid waste management system planning should be based on a variety of inexact programming models which could approach the real-world cases well. Consequently, the characterization and integration of the high uncertain and complex factors and also their interactions in the programming models become the most challenging problems. Moreover, the risk result from the uncertainties that exist in the studied systems should be analyzed and further quantified. To facilitate more robust planning models for municipal solid waste management system, advanced methodologies that can address the uncertainties and complexities, and also quantify the corresponding risk are desired.In this dissertation research, new optimal planning models have been developed in two aspects to well present and slove the high uncertainties and complexities in municipal solid waste management systems. One aspect is to develop new nonlinear, planning models to treat with the municipal solid waste management systems for the effects of "econimies-of-scale"(EOS) and the robustness of the systems; the other is to introduce the queue theory into the interval planning models to deal with the queue phenomenon in the municipal solid waste management systems. Five advanced programming models have been developed for supporting municipal solid waste management systems planning according to different types of uncertainties and complexites in the specific studying system. These models and the associated application fields include:(a) an interval fuzzy robust nonlinear (IFRNLP) model (b) a inexact chance-constraint quadratic solid waste management (1CQSWM) model((c) an queuing-theory-based interval-fuzzy robust two-stage programming model (QB-IRTP)(d) a fuzzy-queue-based interval linear programming model (e) queue-based optimization modelling for planning a municipal aolid waste management system with cost-effective objective and planning in Changchun solid waste management sysytem. In addition, different types and levels of system-failure risks due to the uncertain inputs of the developed model are analyzed and further quantified. For each system, efforts are made in uncertainty characterization and integration, model conceptualization and formulation, solution method-development, risk analysis and quantification, and policy or scenario analysis.Compared with the existing inexact optimization approaches, the developed models are more robust due to the advantages in reflecting high uncertain and complex components presented as fuzzy interval lbound, economies of scale, average arriving rate, average serving rate, wating cost, waiting time. Consequently, the obtained solutions are useful for decision makers to gain insight regarding the tradeoffs among environmental, economic and social criteria. The five developed model have been applied in the municipal solid waste management systems. A series of feasible schemes can be generated based on the interval solutions obtained under different scenarios and risk levels. Decision makers can identify the desired scheme according to the practical situation, such as the risk types and levels they can accept, and their experiences. In other words, the obtained results are adjustable and flexible in real-world cases.