Self-Learning Genetic Algorithm for a Timetabling Problem with Fuzzy Constraints

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17610%2F13%3AA14015ZZ" target="_blank" >RIV/61988987:17610/13:A14015ZZ - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Self-Learning Genetic Algorithm for a Timetabling Problem with Fuzzy Constraints

Popis výsledku v původním jazyce

Timetabling Problem is NP-hard combinatorial optimization problem which lacks analytical solution methods. Here, for solving this problem we present a specific genetic algorithm with fuzzy constraints. Our method incorporates a self-learning genetic algorithm using indirect representation based on event priorities, and heuristic local search operators to tackle real world timetabling problem. By fuzzy sets we measure violation of soft constraints in fitness function to take care of inherent uncertaintyand vagueness involved in real life data. The proposed technique satisfies all hard constraints of problem and achieves significantly better score in satisfying soft constraints. The algorithm is computationally effective as it is demonstrated on a smallrealistic example for which an optimal solution is known by exhaustive calculation. The structure of the algorithm enables parallel computations being necessary for solving large real life problems.

Název v anglickém jazyce

Self-Learning Genetic Algorithm for a Timetabling Problem with Fuzzy Constraints

Popis výsledku anglicky

Timetabling Problem is NP-hard combinatorial optimization problem which lacks analytical solution methods. Here, for solving this problem we present a specific genetic algorithm with fuzzy constraints. Our method incorporates a self-learning genetic algorithm using indirect representation based on event priorities, and heuristic local search operators to tackle real world timetabling problem. By fuzzy sets we measure violation of soft constraints in fitness function to take care of inherent uncertaintyand vagueness involved in real life data. The proposed technique satisfies all hard constraints of problem and achieves significantly better score in satisfying soft constraints. The algorithm is computationally effective as it is demonstrated on a smallrealistic example for which an optimal solution is known by exhaustive calculation. The structure of the algorithm enables parallel computations being necessary for solving large real life problems.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

<a href="/cs/project/ED1.1.00%2F02.0070" target="_blank" >ED1.1.00/02.0070: Centrum excelence IT4Innovations</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2013

Kód důvěrnosti údajů

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

Název periodika

INT J INNOV COMPUT I

ISSN

1349-4198

e-ISSN

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Svazek periodika

9

Číslo periodika v rámci svazku

11

Stát vydavatele periodika

JP - Japonsko

Počet stran výsledku

18

Strana od-do

4565-4582

Kód UT WoS článku

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EID výsledku v databázi Scopus

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