Grey quadratic programming and its application to municipal solid waste management planning under uncertainty

This paper introduces a grey quadratic programming (GQP) method as a means for decision making under uncertainty. The method improves upon existing grey linear programming (GLP) methods by allowing the consideration of the effects of economies of scale on cost coefficients in the objective function. The approach also has advantages over a grey nonlinear programming method, since a global optimum is obtainable and the model is moderately easy to solve through commercially available quadratic programming packages. The modelling approach is applied to a hypothetical problem of waste flow allocation within a municipal solid waste management system. The results indicate that, compared with the GLP method, GQP provides a more effective means for reflecting system cost variations and may therefore generate more realistic and applicable solutions.