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Pregled bibliografske jedinice broj: 942285

Rad u postupku objavljivanja

Autori: Domović, Daniel; Rolich, Tomislav; Golub, Marin
Naslov: Hyper-heuristic Approach for Improving Marker Efficiency
Izvornik: AUTEX research journal (1470-9589) (2018)
Status rada: prihvaćen
Ključne riječi: Marker making ; Production optimization ; Hyper-heuristic
Sažetak:
Marker planning is an optimization arrangement problem, where a set of cutting parts need to be placed on a marker so the cutting parts do not overlap, and do not exceed the boundaries of a marker. An optimal marker that utilizes fabric length has to be obtained. The aim of this research was to develop novel algorithms for obtaining an efficient marker that would achieve competitive results and optimize the garment production. In this research a novel Grid heuristic is introduced for obtaining a marker, alongside improvement methods: Grid-BLP and Grid-Shaking. These algorithms were combined with genetic algorithm that determines the placement order of cutting parts using All Equal First (AEF) order. A novel individual representation for genetic algorithm has been designed that is consisted of order sequence, rotation detection and the choice of placement algorithm (hyper-heuristic). Experiments were conducted to determine the best marker making method, and hyper-heuristic efficiency. The implementation and experiments were conducted in MATLAB using GEATbx toolbox on five datasets from textile industry: ALBANO, DAGLI, MAO, MARQUES and MAN SHIRT. Lay plan efficiency in percentage was recorded with best results: 84.50%, 80.13%, 79.54%, 84.67% and 86.02% obtained for the datasets respectively.
Rad je indeksiran u
bazama podataka:
Current Contents Connect (CCC)
Scopus
SCI-EXP, SSCI i/ili A&HCI
Science Citation Index Expanded (SCI-EXP) (sastavni dio Web of Science Core Collectiona)
Projekt / tema: HRZZ-IP-2013-11-3011
Izvorni jezik: ENG
Kategorija: Znanstveni
Znanstvena područja:
Računarstvo,Tekstilna tehnologija
Upisao u CROSBI: Daniel Domović (daniel.domovic@ttf.hr), 11. Lip. 2018. u 00:15 sati



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