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A discrete spotted hyena optimizer for solving distributed job shop scheduling problems

Applied Soft Computing · Temmuz 2021

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YÖKSİS Kayıtları
A discrete spotted hyena optimizer for solving distributed job shop scheduling problems
APPLIED SOFT COMPUTING · 2021 SCI-Expanded
Doç. Dr. MEHMET AKİF ŞAHMAN →
YÖKSİS ISSN Eşleşmesi

Bu dergide (ISSN eşleşmesi) kurumun 17 kaydı bulundu.

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Color image segmentation based on multiobjective artificial bee colony optimization
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Liver fibrosis staging using CT image texture analysis and soft computing
2014 ISSN: 15684946 SCI-Expanded
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2018 ISSN: 1568-4946 SCI Q1
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A hybrid binary grey wolf optimizer for selection and reduction of reference points with extreme learning machine approach on local GNSS/leveling geoid determination
2021 ISSN: 1568-4946 SCI-Expanded Q1
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Boosting the oversampling methods based on differential evolution strategies for imbalanced learning
2021 ISSN: 1568-4946 SCI-Expanded Q1
Doç. Dr. AHMET CEVAHİR ÇINAR →
A discrete spotted hyena optimizer for solving distributed job shop scheduling problems
2021 ISSN: 1568-4946 SCI-Expanded Q1
Doç. Dr. MEHMET AKİF ŞAHMAN →
A hybrid binary grey wolf optimizer for selection and reduction of reference points with extreme learning machine approach on local GNSS/leveling geoid determination
2021 ISSN: 1568-4946 SCI-Expanded Q1
Doç. Dr. MEHMET AKİF ŞAHMAN →
Boosting the oversampling methods based on differential evolution strategies for imbalanced learning
2021 ISSN: 1568-4946 SCI-Expanded Q1
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Classification rule mining based on Pareto-based Multiobjective Optimization
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Classification rule mining based on Pareto-based Multiobjective Optimization
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Makale Bilgileri

Dergi Applied Soft Computing
ISSN15684946
Yayın TarihiTemmuz 2021
Cilt / Sayfa106
DOI10.1016/j.asoc.2021.107349
Scopus ID2-s2.0-85103695362
Özet Scheduling is an important decision-making process for manufacturing companies. Shop scheduling is a subsection of scheduling related to manufacturing shops. The job shop scheduling problem (JSP) aims to minimize the makespan of a product value of the production process. This issue is related to optimizing the sequence of the jobs on appropriate machines. With globalization, manufacturing shops are scattered around the world. The distributed job shop scheduling problem (DJSP) tries to solve the optimizing sequence on these scattered facilities. DJSP is more complex than JSP. DJSP is solved by exact and heuristic solvers. Exact solvers more time-consuming processes for huge problems. In this work, a discrete version of the spotted hyena optimizer (DSHO) is proposed for solving DJSP. A workload-based facility order mechanism and a greedy heuristic approach are combined with the DSHO algorithm. 80 distributed job shop scheduling problems (DJSP) are solved by DSHO. For evaluating the performance of the DSHO, numerical results of the 480 (2 facilities to 7 facilities) large instances that are derived from well-known JSP benchmarks are compared with four different discrete meta-heuristic algorithms. The experimental results are shown that DSHO is a pioneer solver for DJSP.

Yazarlar (1)

1
Mehmet Akif Şahman

Anahtar Kelimeler

Discrete spotted hyena optimizer Discrete swarm intelligence Distributed job shop scheduling Job shop scheduling Spotted hyena optimizer

Kurumlar

Selçuk Üniversitesi
Selçuklu Turkey
Scimago Dergi (ISSN Eşleşmesi)
Applied Soft Computing
Q1
SJR Skoru1,511
H-Index208
YayıncıElsevier B.V.
ÜlkeNetherlands
Software (Q1)
Dergi sayfasına git

Metrikler

64
Atıf
1
Yazar
5
Anahtar Kelime

Sistemimizdeki Yazarlar

MŞ
MEHMET AKİF ŞAHMAN
Doç. Dr.

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