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contributor authorRenbin Xiao
contributor authorZhenwu Tao
contributor authorYong Liu
date accessioned2017-05-09T00:15:37Z
date available2017-05-09T00:15:37Z
date copyrightMarch, 2005
date issued2005
identifier issn1530-9827
identifier otherJCISB6-25953#18_1.pdf
identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/131491
description abstractThis paper presents a new method to isomorphism identification based on two novel evolutionary approaches—ant algorithm (AA) and artificial immune system (AIS). Salient features of the two evolutionary approaches are their efficient, robust and general-purpose algorithms for isomorphism identification despite its nondeterministic polynomial (NP) hard nature. First, based on the rearrangement of the vertexes in kinematic chains, the isomorphism identification of kinematic chains is transformed into a degree-reducible traveling salesman problem (TSP), so that the dimension and complexity can be largely decreased. Then AA and AIS algorithms are adopted to solve the transformed TSP. At last, characteristics of the two evolutionary approaches are discussed based on case studies.
publisherThe American Society of Mechanical Engineers (ASME)
titleIsomorphism Identification of Kinematic Chains Using Novel Evolutionary Approaches
typeJournal Paper
journal volume5
journal issue1
journal titleJournal of Computing and Information Science in Engineering
identifier doi10.1115/1.1846057
journal fristpage18
journal lastpage24
identifier eissn1530-9827
keywordsAlgorithms AND Chain
treeJournal of Computing and Information Science in Engineering:;2005:;volume( 005 ):;issue: 001
contenttypeFulltext


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