Annealing Based Integer Optimization Heuristic with Levy Flights

Kód výsledku v IS VaVaI

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Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Annealing Based Integer Optimization Heuristic with Levy Flights

Popis výsledku v původním jazyce

Novel population based integer optimization heuristic yields from the theory of Mean Field Annealing. Population center and covariance matrix are estimated for given annealing temperature and then used as directional correction of Levy Flight mutation. The heuristic is of competitive nature like Competitive Differential Evolution. Here, nine Levy Flight mutations compete and are selected according to their success. Resulting heuristic has four parameters: population size, regularization factor, annealing temperature and Levy Flight temperature. Depending on the task complexity there is a relationship between searching efficiency and regularization, annealing and heavy-tailed flights. This heuristic is suitable integer optimization tasks with many local extremes. One of them is the clustering problem which can be converted to optimum partition with any penalization function. The clustering can help to classify various states of stock market system according to time series analysis and is used for the demonstration of novel heuristic.

Název v anglickém jazyce

Annealing Based Integer Optimization Heuristic with Levy Flights

Popis výsledku anglicky

Novel population based integer optimization heuristic yields from the theory of Mean Field Annealing. Population center and covariance matrix are estimated for given annealing temperature and then used as directional correction of Levy Flight mutation. The heuristic is of competitive nature like Competitive Differential Evolution. Here, nine Levy Flight mutations compete and are selected according to their success. Resulting heuristic has four parameters: population size, regularization factor, annealing temperature and Levy Flight temperature. Depending on the task complexity there is a relationship between searching efficiency and regularization, annealing and heavy-tailed flights. This heuristic is suitable integer optimization tasks with many local extremes. One of them is the clustering problem which can be converted to optimum partition with any penalization function. The clustering can help to classify various states of stock market system according to time series analysis and is used for the demonstration of novel heuristic.

Druh

D - Stať ve sborníku

CEP obor

BB - Aplikovaná statistika, operační výzkum

OECD FORD obor

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Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2016

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Mathematical Methods in Economics 2016

ISBN

978-80-7494-296-9

ISSN

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e-ISSN

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Počet stran výsledku

6

Strana od-do

576-581

Název nakladatele

Technical University of Liberec

Místo vydání

Liberec

Místo konání akce

Liberec

Datum konání akce

6. 9. 2016

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000385239500099