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.

中文翻译：

---

基于帕累托遗传算法的聚合物技术在注塑模具加热棒布局确定中的应用进展

基于帕累托的遗传算法是解决工程中复杂优化设计问题的有效途径。本研究首先介绍了帕累托最优解和多目标遗传算法的原理。其次，为了研究模具温度对产品性能的影响，设计了一种多腔实验注塑模具，其温度可以通过加热棒进行控制。为了在加热阶段后在多腔表面上获得均匀的温度分布，基于模具的传热过程建立了加热棒布局的多目标优化模型。最后结合基于Pareto的遗传算法和有限元方法对优化后的模型进行求解，得到最优解。