20.500.12556/DKUM-46823 PRILAGODLJIVI EVOLUCIJSKI ALGORITEM ZA RAZPOREJANJE PROIZVODNJE V DINAMIČNEM OKOLJU ADAPTIVE EVOLUTION ALGORITHM FOR PRODUCTION SCHEDULING IN DYNAMIC ENVIRONMENT V doktorski disertaciji obravnavamo problem razporejanja proizvodnje, ki v proizvodnih podjetjih predstavlja enega glavnih problemov, saj lahko prihaja do vsakodnevnih sprememb zaradi novih naročil, okvar strojev, zamud v nabavi, itd. Ker je razporejanje že v osnovi zahtevno opravilo, te spremembe lahko privedejo do zastojev proizvodnje, kar pa si podjetja ne morejo privoščiti. V okviru doktorske disertacije smo razvili evolucijski algoritem, ki temelji na evoluciji in uporabi demutacij, selektivnih mutacij in prilagodljive kriterijske funkcije in se uporablja za reševanje razporejanja proizvodnje (job shop scheduling) po kriteriju minimalnega izvršnega časa. V raziskavi smo pokazali, da z uporabo demutacij, selektivnih mutacij in prilagodljive kriterijske funkcije dosežemo učinkovitejši algoritem za reševanje razporejanja proizvodnje. Predlagani algoritem smo testirali na podatkih iz realnega okolja in na znanih problemskih instancah. Rezultate predlaganega algoritma smo prav tako primerjali z obstoječimi sorodnimi algoritmi iz literature in pokazali, da je algoritem konkurenčen omenjenim algoritmom glede na doseganje najkrajšega izvršnega časa. V okviru raziskave je bil razvit tudi sistem za izvoz podatkov iz informacijskega sistema Perftech Largo v algoritmu razumljivo skripto in kasnejša objava razporedov na internetnem portalu, ki omogoča vsem vpletenim v sam proces proizvodnje (tako planerju kot izvajalcem), natančen vpogled v trenutno stanje proizvodnje. Scheduling represents one of the biggest issues in production process, because of daily changes that are a consequence of new orders, machines' malfunctions, delays in purchasing, etc. Since scheduling is demanding regardless of those changes, this can lead to delays in production which are unaccaptable for companies in today's world. Within this thesis, we developed an evolution algorithm, based on evolution and the usage of de-mutation, selective mutations and adaptive fitness function, and is used for solving production scheduling (job shop scheduling) based on the criteria of the shortest execution time. In our reseserch we proved that using demutations, selective mutations and adaptive fitness function we can achieve more efficitent algorithm to solve production scheduling. Suggested algorithm was tested on data from real environment and on known benchmark instances. Results of our suggested algoritm were also compared to an existing related algorithms from literature and they show that our algorithm is compatitive. A system for data export from information system Perftech Largo was developed within our research to help users create a script for our algorithm. We also created an internet portal for companies to publish their production schedules. This way all people involved into process can get a detailed insight about the current status of production. evolucijski algoritem razporejanje proizvodnje optimizacija demutacija selektivna mutacija prilagodljiva kriterijska funkcija evolution algorithm production scheduling optimization de-mutations selective mutation adaptive fitnes function. true true false Slovenski jezik Angleški jezik Doktorska disertacija 2014-11-12 15:10:00 2015-03-12 09:56:50 2022-05-19 03:06:14 2021-05-05 03:32:10 2014 0 Maribor 0 0000-00-00 NiDoloceno NiDoloceno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 278313472 URN:SI:UM:DK:HNCCL9JM DOK_Ogris_Vid_2015.pdf DOK_Ogris_Vid_2015.pdf 1 B72986E897B3D0CDF27045B4088E0667 9db935b6387a18030333ae306436dd8b622ba6fafb75fc3b4fb680a06980fc2b 8c65c5ce-7c0b-11eb-bb7a-00155d0001ca https://dk.um.si/Dokument.php?lang=slv&id=70095 Fakulteta za organizacijske vede 0 0 0