doi:10.3808/jei.200300014
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Combining Simulation with Evolutionary Algorithms for Optimal Planning Under Uncertainty: An Application to Municipal Solid Waste Management Planning in the Reginonal Municipality of Hamilton-Wentworth

J. S. Yeomans1*, G. H. Huang2 and R. Yoogalingam1

  1. Management Science Area, Schulich School of Business, York University, Toronto, ON M3J 1P3, Canada
  2. Faculty of Engineering, University of Regina, Regina, SK S4S 0A2, Canada

*Corresponding author. Email: syeomans@schulich.yorku.ca

Abstract


Many uncertain factors exist in the planning for Municipal Solid Waste (MSW) management. In this paper, for the first time an evolutionary algorithm is combined with simulation to determine solutions for the MSW management problem. This new procedure is applied to real case data taken from the Regional Municipality of Hamilton-Wentworth in the province of Ontario and the solutions are compared to the outputs from an earlier study. It can be shown that improved solutions to this problem can be obtained and that this approach provides many practical planning and implementation benefits for problems operating under uncertain conditions.

Keywords: Decision making under uncertainty, genetic algorithms, municipal solid waste management, simulation


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