文章基本信息

标题：Automatic design of algorithms for the traveling salesman problem
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作者：Cristian Loyola ; Mauricio Sepúlveda ; Mauricio Solar 等
期刊名称：Cogent Engineering
电子版ISSN：2331-1916
出版年度：2016
卷号：3
期号：1
页码：1255165
DOI：10.1080/23311916.2016.1255165
语种：English
出版社：Taylor and Francis Ltd
摘要：Abstract The automatic generation of procedures for combinatorial optimization problems is emerging as a new alternative to address the hardest problems of this class. One of these problems still offering great computational difficulty is the traveling salesman problem. Its simple presentation masks the great difficulty that exists when solving it numerically. The results obtained so far for this problem are based on the hybridization of known heuristics. However, there is still a need for an experimental breakthrough in the study of all of the possible combinations of heuristics, which represents a huge search space. In this paper, we explore this space using evolutionary computing to automatically design new algorithms for the problem. We carried out a computational experiment to produce the algorithms that not only are competitive with some of the existing heuristics but that also contain several novel structures that directly influence performance.
关键词：traveling salesman problem ; automatic algorithm design ; heuristics; hyperheuristics; genetic programming; evolutionary computing