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The Pareto-based genetic algorithm is an effective way to solve complex optimization design problems in engineering. In this study, first, the principles of Pareto optimal solutions and multiobjective genetic algorithm were presented. Second, to investigate the influence of the mold temperature on the products’ performances, a multicavity experiment injection mold was designed whose temperature could be controlled by the heating rods. To obtain a homogeneous temperature distribution across the multicavity surfaces after the heating stage, multiobjective optimization models for the heating rods layout were established based on the heat transfer process of the mold. Finally, the Pareto-based genetic algorithm and finite element method were combined to solve the optimized models to obtain the optimal solution. After a finite element analysis and experimental injection, it is proved that the optimized distribution of the heating rods in the mold is necessary for the experiment and production.

Advances in Polymer Technology Application of Pareto-Based Genetic Algorithm in Determining Layout of Heating Rods for a Plastic Injection Mold