CAPACITY PLANNING FOR AN INTEGRATED WASTE MANAGEMENT-SYSTEM UNDER UNCERTAINTY - A NORTH-AMERICAN CASE-STUDY

In this paper, a grey integer-programming (GIP) formulation for the ca pacity planning of an integrated waste management system under uncerta inty is applied to a North American case study,The GIP model is formul ated by introducing concepts of grey systems and grey decisions into a mixed integer linear programming (MILP) framework. The approach has a n advantage in that uncertain information (presented as interval numbe rs) can be effectively communicated into the optimization processes an d resulting solutions, such that feasible decision alternatives can be generated through interpretation and analysis of the grey solutions a ccording to projected applicable system conditions. Moreover, the GIP solution algorithm does not lead to more complicated intermediate mode ls, and thus has lower computational requirements than other integer-p rogramming methods that deal with uncertainties. The proposed model is used for the long-term planning of waste management facility expansio n/utilization in the Regional Municipality of Hamilton-Wentworth (RMHW ), Ontario, Canada. The binary decision variables in the model represe nt the ranges of facility expansion/development alternatives within a multi-period, multi-facility and multi-scale context, and the grey con tinuous variables represent waste flows along the routes connecting th e municipalities and the waste management facilities. The results indi cate that reasonable solutions have been generated through this grey m athematical programming approach. The case study results are potential ly useful for MSW decision-makers in the RMHW for the long-term planni ng of the Region's waste management activities and for formulating rel ated local policies/regulations regarding waste generation and managem ent, and may stimulate the interest of waste management professionals in other jurisdictions on the use of this type of modelling approach f or their specific long-range planning applications. (C) 1997 ISWA.