Abstract
The objective of this paper is to use evolutionary algorithm for policy making to help in decision support, the Regional Integrated Climate-Economy (RICE) model for the dynamic climate change is used to optimize the tradeoff policy between abating of carbon dioxide emissions to reduce global climate change and in the other hand the resulting in economic damages. A Constrained Genetic Algorithms (CGAs) is modified to search for near global optimal solutions the by searching climate optimum control parameters that resulted in optimal CO2 abatement and temperature reduction with less economic damages. A Comparison study between optimizing the output of GAs with the standard solution revealed that GAs successfully found a better solution, in term of finding optimum values for the carbon prices that lead to more reduction in carbon emission comparing to solutions given by the model developer.
Highlights
Green House Gases (GHGs) emissions are presently changing the energy balance of our planet, by trapping heat that would otherwise be radiated out into space
Shows that Carbon prices in the different runs compared with the original Nordhaus results Fig. 3 shows temperature profile presenting slight reduction obtained by the GA
Results presented in this article were successfully attained by optimizing carbon price policy by taking into account the Welfare with minimum environmental damage using constrained GAs
Summary
Green House Gases (GHGs) emissions are presently changing the energy balance of our planet, by trapping heat that would otherwise be radiated out into space. Fading carbon dioxide emissions will definite reduces global climate change, but it is in other hand resulting in economic damages.
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