تجزیه و تحلیل تصمیم گیری چند معیاره یکپارچه و روش برنامه ریزی خطی عدد صحیح مختلط نادرست برای مدیریت مواد زائد جامد شهری

This paper reports on an integration of multi-criteria decision analysis (MCDA) and inexact mixed integer linear programming (IMILP) methods to support selection of an optimal landfill site and a waste-flow-allocation pattern such that the total system cost can be minimized. Selection of a landfill site involves both qualitative and quantitative criteria and heuristics. In order to select the best landfill location, it is often necessary to compromise among possibly conflicting tangible and intangible factors. Different multi-objective programming models have been proposed to solve the problem. A weakness with the different multi-objective programming models used to solve the problem is that they are basically mathematical and ignore qualitative and often subjective considerations such as the risk of groundwater pollution as well as other environmental and socio-economic factors which are important in landfill selection. The selection problem also involves a change in allocation pattern of waste-flows required by construction of a new landfill. A waste flow refers to the routine of transferring waste from one location in a city to another. In selection of landfill locations, decision makers need to consider both the potential sites that should be used as well as the allocation pattern of the waste-flow at different periods of time. This paper reports on our findings in applying an integrated IMILP/MCDA approach for solving the solid waste management problem in a prairie city. The five MCDA methods of simple weighted addition, weighted product, co-operative game theory, TOPSIS, and complementary ELECTRE are adopted to evaluate the landfill site alternatives considered in the solid waste management problem, and results from the evaluation process are presented.

A solid waste management program often involves conflicting economical, environmental, and socio-ecological impacts. For example, locating a new site for landfill development at minimal cost is feasible, but the tradeoff could be the likelihood of groundwater pollution. The question then arises as to how the decision maker can reach a compromise among the conflicting impacts and select the optimal landfill location. The landfill selection problems have often been tackled using multi-criteria decision analysis (MCDA). For example, Hipel (1982) proposed an early version of multi-criteria modelling that incorporated fuzzy set theory and applied the method to a solid-waste disposal problem in Canada. Chen et al. (1997) developed the fuzzy DRASTIC for landfill siting which used a geological information system (GIS) to evaluate potential sites in Taiwan. A different approach is adopted by Hokkanen et al. (1997) who applied a MCDA method called PROMETHEE for facility allocation. Hokkanen et al. (1994) and Vuk et al. (1991) also demonstrated effectiveness of using MCDA methods to solve the selection problem in solid-waste management. In this paper, we present our work in locating a new and optimal landfill site in the city of Regina that would cause the least negative economical and socio-environmental impacts. Multi-objective linear programming (MOLP) models are applicable for handling this type of problems, but the complexity of constructing a MOLP model and the lengthy computation involved render such models inconvenient. A weaknesses in MOLP modelling is that after the result from MOLP has been generated, further analysis may still be required. Also, a MOLP model cannot support input parameters for landfill selection which are based on the subjective opinions of the decision maker or analyst and which can change over time. Therefore, an integration of MCDA with a single-objective linear programming model is proposed to deal with the landfill allocation problem. First, inexact mixed integer linear programming (IMILP) is applied to determine the waste flow in Regina with an objective of minimizing the total cost. Then the total cost and other criteria will be taken into account in a MCDA model in order to determine the best landfill site alternative. In the rest of the paper, Section 2 provides an overview of the problem of selection of a new landfill in the city of Regina. In Section 3, the proposed integrated approach is described. Section 4 discusses considerations on how to deal with uncertainties in the problem. 5 and 6 describe the formulation of IMILP and MCDA models that are applied in the problem, and the result from the analysis is discussed in Section 7. A brief conclusion is given in Section 8.

This paper presents an integrated IMILP/MCDA approach for solving the solid-waste management problem in the city of Regina. In the past, landfill selection problems were solved by applying various unstructured tradeoff approaches which compare only a few criteria simultaneously. This approach may result in process-redundancy and inefficiency. Also, a decision maker's subjective preference is usually not reflected in the decision making process. The integrated IMILP–MCDA approach addresses these shortcomings and renders the selection process more systematic and accountable, while allowing the decision maker to include his/her preferences in the decision-making process. By applying IMILP, the waste flows can be determined with reasonable computational effort. Compared with other multi-objective programming approaches, the integrated IMILP/MCDA approach effectively incorporates subjective judgment from the decision maker. Furthermore, since each MCDA method reflects different characteristics and assumptions, and using a single method may not give satisfactory results, it is advisable to apply several MCDA methods to deal with a given selection problem. For example, the CGT method might not be suited for the landfill siting problem because it favors only one alternative and does not differentiate among the rest. In this paper, since five MCDA methods are applied and the results have been aggregated, the final ranking of the alternatives is considered reliable and adequately reflects consideration of the various criteria as well as the decision maker's subjective preferences.