A GRAY FUZZY LINEAR-PROGRAMMING APPROACH FOR MUNICIPAL SOLID-WASTE MANAGEMENT PLANNING UNDER UNCERTAINTY

This paper proposes a new mathematical programming method-grey fuzzy l inear programming (GFLP)-as a means for optimization analysis under un certainty. The method improves upon previous grey linear programming ( GLP) and flexible fuzzy linear programming (FLP) methods by allowing u ncertainty in both the model coefficients and stipulations to be effec tively communicated into the optimization process, and thus provide mo re satisfactory solutions for an optimization problem under uncertaint y. Compared with the ordinary GLP method, grey solutions with smaller variations are provided, which may be useful when model inputs are ver y uncertain. Compared with existing flexible FLP methods, more uncerta in information is incorporated within the GFLP model, and the toleranc e interval of the objective function value can be determined quantitat ively. The modelling approach is applied to a hypothetical problem in the municipal solid waste management planning area. The results indica te that, compared with the solutions from a GLP model, the ranges of v alues for the objective function and the majority of the decision vari ables are decreased. Therefore, the developed GFLP method can be consi dered as a feasible approach for increasing system certainty and achie ving more applicable and satisfactory grey solutions.