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Engineering an efficient two-phase local search algorithm forthe co-rotating twin-screw extruder configuration problem

机译:针对同向旋转双螺杆挤出机配置问题设计有效的两阶段本地搜索算法

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摘要

The twin-screw configuration problem arises during polymer extrusion and compounding. It consists in defining the location of a set of pre-defined screw elements along the screw axis in order to optimize different, typically conflicting objectives. In this paper, we present a simple yet effective stochastic local search (SLS) algorithm for this problem. Our algorithm is based on efficient single-objective iterative improvement algorithms, which have been developed by studying different neighborhood structures, neighborhood search strategies, and neighborhood restrictions. These algorithms are embedded into a variation of the two-phase local search framework to tackle various bi-objective versions of this problem. An experimental comparison with a previously proposed multi-objective evolutionary algorithm shows that a main advantage of our SLS algorithm is that it converges faster to a high-quality approximation to the Pareto front.
机译:双螺杆构型问题在聚合物挤出和复合过程中出现。它在于定义一组预定义的螺钉元素沿螺钉轴线的位置,以优化不同的,通常相互冲突的目标。在本文中,我们针对此问题提出了一种简单而有效的随机局部搜索(SLS)算法。我们的算法基于有效的单目标迭代改进算法,该算法是通过研究不同的邻域结构,邻域搜索策略和邻域限制而开发的。这些算法被嵌入到两阶段本地搜索框架的变体中,以解决该问题的各种双目标版本。与先前提出的多目标进化算法进行的实验比较表明,我们的SLS算法的主要优势在于,它收敛速度更快,可以逼近Pareto前沿的高质量近似值。

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