An Evolutionary Grey, Hop, Skip, and Jump Approach: Generating Alternative Policies for the Expansion of Waste Management

Abstract

Evolutionary simulation-optimization methods are combined with a Grey Hop, Skip, and Jump (GHSJ) approach in an application to municipal solid waste management planning. GHSJ techniques have been effectively applied to problems containing uncertain information. Simulation-optimization methods can be adapted to a wide variety of problem types in which some or all of the system components are stochastic. In this paper, the advantages from both of these techniques are combined and used for efficiently generating improved decision alternatives. An illustrative application of the method is provided to demonstrate the usefulness of this approach in the planning design phase for the expansion of a waste management system. By using this approach, multiple different planning alternatives can be created that meet established system criteria, while simultaneously remaining acceptable and implementable in practice. Solid waste decision makers faced with difficult and controversial choices would then interpret and analyze these alternatives to internalize the environmental-economic tradeoffs prior to selecting their final policy.

Keywords: Public sector decision making under uncertainty, simulation, evolutionary algorithms, waste management planning, modelling to generate alternatives