GREY INTEGER PROGRAMMING - AN APPLICATION TO WASTE MANAGEMENT PLANNING UNDER UNCERTAINTY

This paper introduces a grey integer programming (GIP) method for faci lity expansion planning under uncertainty, by incorporating the concep ts of grey number and grey mathematical programming into a mixed integ er linear programming optimization framework. The approach is an impro vement upon previous integer programming methods in terms of its techn ical characteristics and applicability. It allows uncertain informatio n to be effectively communicated into the optimization process and the resulting solutions. It also has low computational requirements and i s thus applicable to practical problems. The modelling approach is app lied to a hypothetical planning problem of waste flow allocation and t reatment/disposal facility expansion within a regional solid waste man agement system. The binary variable solutions provide the ranges of di fferent development alternatives within a multi-period, multi-facility and multi-scale context, and the continuous variable solutions provid e optimal schemes for waste flow allocation corresponding to the upper and lower bounds of the objective function value. The results indicat e that reasonable and useful solutions can be achieved through the dev eloped approach.