Using of Genetic Algorithms in Design of Hybrid Integrated Circuits

Korpyljov, D.; Свиридова, Т. В.; Tkachenko, Serhiy

doi:10.1109/cadsm.2007.4297557

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Evolutionary-fragmentary Model Of the Problem1

Introduction1

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2015

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“…The added letter is deleted from the list. The labor input of this algorithm does not exceed O n ( ) 4 .…”

Section: Evolutionary-fragmentary Model Of the Problemmentioning

confidence: 99%

“…For such problems, application of various metaheuristics such as evolutionary models is justified. Evolutionary models and genetic algorithms are often used to find approximate optimal solutions to various statements of routing problems [1][2][3][4][5][6][7].…”

Section: Introductionmentioning

confidence: 99%

“…9 8 7 6 5 4 3 2 1 9 8 7 6 5 4 3 2 2 9 9 9 9 9 9 9 9 9 9 8 8 8 8 8 8 8 8 9 8 7 7 7 7 7 7 7 9 8 7 6 6 6 6 6 6 9 8 7 6 5 5 5 5 5 9 8 7 6 5 4 4 4 4 9 8 7 6 5 4 3 3 3 Fig. 4. Routing with density 7 on an 11 11 lattice.…”

mentioning

confidence: 99%

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Evolutionary-Fragmentary Model of the Routing Problem

2015

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One of the variants of the routing problem on a plane integer lattice is considered. It is shown that this problem can be represented as a problem of searching for words with certain properties over a finite alphabet. In turn, the problem of finding optimal words can be considered as a problem of fragmentary structure. A combinatorial estimate for the set of feasible words is derived and the lower bound of the density is established for the problem of finding optimal line density. An evolutionary-fragmentary model of the routing problem is constructed. Optimal and near-optimal solutions are obtained for this problem for small dimensions.

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“…The added letter is deleted from the list. The labor input of this algorithm does not exceed O n ( ) 4 .…”

Section: Evolutionary-fragmentary Model Of the Problemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%