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Genetic processing of the traveling salesman problem with the associative architecture AM/sup 3/

机译:关联架构AM / sup 3 /对旅行商问题的遗传处理

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This paper presents a genetic solving approach to the Traveling Salesman Problem (TSP), which can be significantly accelerated by using an associative processor architecture, called the AM/sup 3/. To compile the genetic TSP algorithm, a C/sup ++/ programming environment containing an associative object library is needed as well as an AM/sup 3/ code interpreter to count machine instructions. Further, a recombination operator, known in the literature as "Partially Mapped Crossover" (PMX), is employed. The associative character of this operator makes it possible to reduce its time complexity from quadratic to linear (from O(n/sup 2/) to O(n)). This reduction is noticeable in practice, since genetical recombination demands an increasing portion of the total run-time with growing problem size. As the TSP can be seen as a typical representative of permutation problems, it is assumed that the combination of genetic and associative processing is suitable for similar applications.
机译:本文提出了旅行商问题(TSP)的遗传求解方法,该方法可以通过使用称为AM / sup 3 /的关联处理器体系结构来显着加速。要编译遗传TSP算法,需要一个包含关联对象库的C / sup ++ /编程环境以及一个AM / sup 3 /代码解释器来对机器指令进行计数。此外,使用在文献中称为“部分映射的交换”(PMX)的重组算子。该运算符的关联特性可以将其时间复杂度从二次降低为线性(从O(n / sup 2 /)到O(n))。这种减少在实践中是很明显的,因为基因重组需要增加总运行时间的一部分,并且问题的大小也要增加。由于TSP可以看作是置换问题的典型代表,因此可以假定遗传处理和关联处理的组合适用于类似的应用程序。

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