Pregled bibliografske jedinice broj: 1211835
On the Application of ϵ-Lexicase Selection in the Generation of Dispatching Rules
On the Application of ϵ-Lexicase Selection in the Generation of Dispatching Rules // 2021 IEEE Congress on Evolutionary Computation
Kraków, Poljska: Institute of Electrical and Electronics Engineers (IEEE), 2021. str. 2152-2132 doi:10.1109/CEC45853.2021.9504982 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 1211835 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
On the Application of ϵ-Lexicase Selection in the
Generation of Dispatching Rules
Autori
Planinić, Lucija ; Đurasević, Marko ; Jakobović, Domagoj
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
2021 IEEE Congress on Evolutionary Computation
/ - : Institute of Electrical and Electronics Engineers (IEEE), 2021, 2152-2132
ISBN
978-1-7281-8394-7
Skup
IEEE Congress on Evolutionary Computation (CEC 2021))
Mjesto i datum
Kraków, Poljska, 28.06.2021. - 01.07.2021
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
lexicase ; genetic programming ; dispatching rules ; scheduling
Sažetak
Dynamic online scheduling is a difficult problem which commonly appears in the real world. This is because the decisions have to be performed in a small amount of time using only currently available incomplete information. In such cases dispatching rules (DRs) are the most commonly used methods. Since designing them manually is a difficult task, this process has been successfully automatised by using genetic programming (GP). The quality of the evolved rules depends on the problem instances that are used during the training process. Previous studies demonstrated that careful selection of problem instances on which the solutions should be evaluated during evolution improves the performance of the generated rules. This paper examines the application of the ε-lexicase selection to the design of DRs for the unrelated machines scheduling. This selection offers a better solution diversity since the individuals are selected based on a smaller subset of instances, which leads to the creation of DRs that perform well on the selected instances. The experiments demonstrate that this type of selection can significantly improve the results for the Roulette Wheel and Elimination GP variants, while achieving the same performance as the Steady State Tournament GP. Furthermore, the ε-lexicase based algorithms have a better convergence rate, which means that the increased diversity in the population has a positive effect on the evolution process.
Izvorni jezik
Engleski
Znanstvena područja
Računarstvo
POVEZANOST RADA
Projekti:
HRZZ-IP-2019-04-4333 - Hiperheurističko oblikovanje pravila raspoređivanja (HyDDRa) (Jakobović, Domagoj, HRZZ ) ( CroRIS)
Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb
