GREY DYNAMIC-PROGRAMMING FOR WASTE-MANAGEMENT PLANNING UNDER UNCERTAINTY

The present paper introduces a grey dynamic programming (GDP) method b y incorporating concepts of grey systems and grey decisions within a d ynamic programming framework as a means for decision making under unce rtainty. The grey dynamic programming approach improves upon previous dynamic programming methods by allowing uncertain information to be di rectly communicated into the optimization process and resulting soluti ons, such that decision alternatives could be generated through the in terpretation and analysis of the grey solutions according to projected applicable system conditions. The method also does not lead to more c omplicated intermediate models, and thus has reasonable computational requirements and is applicable to practical problems. Application of t he method to a hypothetical problem of waste management facility expan sion/use planning within a municipal-solid-waste management system ind icates that reasonable solutions have been generated. Comparisons betw een grey dynamic programming and other dynamic programming methods are also provided.