An Enhanced Annealing Genetic Algorithm For Multi-objective Optimization Problems
نویسندگان
چکیده
In this paper, we present a new algorithm — an Enhanced Annealing Genetic Algorithm for Multi-Objective Optimization problems (MOPs). The algorithm tackles the MOPs by a new quantitative measurement of the Pareto front coverage quality — Coverage Quotient. We then correspondingly design an energy function, a fitness function and a hybridization framework, and manage to achieve both satisfactory results and guaranteed convergence.
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