Pregled bibliografske jedinice broj: 642272
A Fast Genetic Algorithm Based on Single Gene Evaluation Fitness Mechanism for Job-Shop Scheduling Problem
A Fast Genetic Algorithm Based on Single Gene Evaluation Fitness Mechanism for Job-Shop Scheduling Problem // International Conference on Innovative Technologies IN-TECH / Car, Zlatan ; Kudláček, Jan ; Szalay, Tibor (ur.).
Rijeka: Tehnički fakultet Sveučilišta u Rijeci, 2013. str. 345-348 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 642272 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
A Fast Genetic Algorithm Based on Single Gene Evaluation Fitness Mechanism for Job-Shop Scheduling Problem
Autori
Janeš, Gordan ; Car, Zlatan ; Ogrizović, Dario
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
International Conference on Innovative Technologies IN-TECH
/ Car, Zlatan ; Kudláček, Jan ; Szalay, Tibor - Rijeka : Tehnički fakultet Sveučilišta u Rijeci, 2013, 345-348
ISBN
978-953-6326-88-4
Skup
International Conference on Innovative Technologies IN-TECH
Mjesto i datum
Budimpešta, Mađarska, 10.09.2013. - 13.09.2013
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
JSSP; job-shop scheduling; genetic algorithm; heuristics; fast genetic algorithm; single gene fitness; crossover operator
Sažetak
The Job Shop Scheduling Problem (JSSP) is one of the most general and difficult of all traditional scheduling problems. Search based on traditional ghenetic algorithms has a major drawback: large computational time and memory usage if a large population and / or a large number of generations are used but on the other hand larger population and larger number of generations usualy provide better results. The goal of this research is to develop an efficient scheduling method based on genetic algorithm to address JSSP. In the scheduling method new crossover and selection method are tested. The results are compared with two other two similar and commonly used algorithms. Compared to traditional genetic algorithms, the proposed has significant improvements in solution quality and speed.
Izvorni jezik
Engleski
Znanstvena područja
Računarstvo, Strojarstvo
POVEZANOST RADA
Projekti:
069-1201787-1754 - Numeričko modeliranje, simulacija i optimizacija u oblikovanju lima (Car, Zlatan, MZOS ) ( CroRIS)
Ustanove:
Tehnički fakultet, Rijeka