This paper discusses the solution of a particular case of grey nonlinear programming, the grey quadratic programming (GQP), and introduces the genetic algorithms (GA) approach as a feasible method for solving GQP problems. A framework using genetic algorithm for grey quadratic programming (GAGQP) framework is designed and constructed by generalizing the common components of the GQP solutions and encapsulating the basic GA operations, This framework has been applied on a hypothetical municipal solid waste management problem and the result of the case study indicated that the GA approach is competitive with, if not superior to, other methods in solving GQP problems
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