An analytic expression of relative approximation error for a class of evolutionary algorithms

Jun He

Allbwn ymchwil: Cyfraniad at gynhadleddAralladolygiad gan gymheiriaid

8 Dyfyniadau (Scopus)
145 Wedi eu Llwytho i Lawr (Pure)

Crynodeb

An important question in evolutionary computation is how good solutions evolutionary algorithms can produce. This paper aims to provide an analytic analysis of solution quality in terms of the relative approximation error, which is defined by the error between 1 and the approximation ratio of the solution found by an evolutionary algorithm. Since evolutionary algorithms are iterative methods, the relative approximation error is a function of generations. With the help of matrix analysis, it is possible to obtain an exact expression of such a function. In this paper, an analytic expression for calculating the relative approximation error is presented for a class of evolutionary algorithms, that is, (1+1) strictly elitist evolution algorithms. Furthermore, analytic expressions of the fitness value and the average convergence rate in each generation are also derived for this class of evolutionary algorithms. The approach is promising, and it can be extended to non-elitist or population-based algorithms too.
Iaith wreiddiolSaesneg
Tudalennau4366-4373
Dynodwyr Gwrthrych Digidol (DOIs)
StatwsCyhoeddwyd - Gorff 2016
DigwyddiadIEEE World Congress on Computational Intelligence - Vancouver, Canada
Hyd: 24 Gorff 201629 Gorff 2016

Cynhadledd

CynhadleddIEEE World Congress on Computational Intelligence
Teitl crynoIEEE WCCI 2016
Gwlad/TiriogaethCanada
DinasVancouver
Cyfnod24 Gorff 201629 Gorff 2016

Ôl bys

Gweld gwybodaeth am bynciau ymchwil 'An analytic expression of relative approximation error for a class of evolutionary algorithms'. Gyda’i gilydd, maen nhw’n ffurfio ôl bys unigryw.

Dyfynnu hyn