首页> 外文会议>International Conference on Adaptive and Natural Computing Algorithms; 2005; Coimbra(PT) >A Multi-Objective Evolutionary Algorithm for Solving Traveling Salesman Problems: Application to the Design of Polymer Extruders
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A Multi-Objective Evolutionary Algorithm for Solving Traveling Salesman Problems: Application to the Design of Polymer Extruders

机译:解决旅行商问题的多目标进化算法:在聚合物挤出机设计中的应用

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A Multi-Objective Evolutionary Algorithm (MOEA) for solving Traveling Salesman Problems (TSP) was developed and used in the design of screws for twin screw polymer extrusion. Besides the fact that MOEA for TSP have already been developed, this paper constitutes an important and original contribution, since in this case, they are applied in the design of machines. The Twin-Screw Configuration Problem (TSCP) can be formulated as a TSP. A different MOEA is developed, in order to take into account the discrete nature of the TSCP. The algorithm proposed was applied to some case studies where the practical usefulness of this approach was demonstrated. Finally, the computational results are confronted with experimental data showing the validity of the approach proposed.
机译:开发了用于解决旅行推销员问题(TSP)的多目标进化算法(MOEA),并将其用于双螺杆聚合物挤出的螺杆设计中。除了已经开发出用于TSP的MOEA之外,本文还是一项重要而原始的贡献,因为在这种情况下,它们已被应用于机械设计中。双螺杆配置问题(TSCP)可以表述为TSP。为了考虑到TSCP的离散性,开发了不同的MOEA。所提出的算法被应用于一些案例研究,这些案例证明了这种方法的实用性。最后,计算结果与实验数据相吻合,表明所提出方法的有效性。

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