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A hybrid genetic algorithm for solving energy-efficient mixed-model robotic two-sided assembly line balancing problems with sequence-dependent setup times

Cilt: 30 Sayı: 7 28 Aralık 2024
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A hybrid genetic algorithm for solving energy-efficient mixed-model robotic two-sided assembly line balancing problems with sequence-dependent setup times

Abstract

Serious environmental challenges such as global warming and climate change have captured a growing amount of public awareness in the last decade. Besides monetary incentives, the drive for environmental preservation and the pursuit of a sustainable energy source have contributed to an increased recognition of energy usage within the industrial sector. Meanwhile, the challenge of energy efficiency stands out as a major focal point for researchers and manufacturers alike. Efficient assembly line balancing plays a vital role in enhancing production effectiveness. The robotic two-sided assembly line balancing problem (RTALBP) commonly arises in manufacturing facilities that produce large-sized products in high volumes. In this scenario, multiple robots are placed at each assembly line station to manufacture the product. The utilization of robots is extensive within two-sided assembly lines, primarily driven by elevated labour expenses. However, this adoption has resulted in the challenge of increasing energy consumption. Therefore, in this study, a new hybrid genetic algorithm is introduced, incorporating an adaptive local search mechanism. for the mixed-model robotic two-sided assembly line balancing problems with sequence-dependent setup times. This algorithm has two main objectives: minimizing cycle time (time-based approach) and overall energy consumption (energy-based approach). Depending on managerial priorities, either the time-based or energy-based model can be chosen for different production timeframes.

Keywords

Kaynakça

  1. [1] United Nations Climate Change. “Key aspects of the Paris Agreement” https://unfccc.int/most-requested/key-aspects-of-the-paris-agreement (26.09.2023).
  2. [2] Sun B, Wang L, Peng Z. “Bound-guided hybrid estimation of distribution algorithm for energy-efficient robotic assembly line balancing”. Computers & Industrial Engineering, 146, 1-34, 2020.
  3. [3] Scholl A. Balancing and Sequencing of Assembly lines. 1st ed. Heidelberg, Germany, Physica-Verlag, 1995.
  4. [4] Boysen N, Fliedner M, Scholl A. “Sequencing mixed-model assembly lines: Survey, classification and model critique”. European Journal of Operational Research, 192(2), 349-373, 2009.
  5. [5] Sivasankaran P, Shahabudeen P. “Literature review of assembly line balancing problems”. The International Journal of Advanced Manufacturing Technology, 73(9-12), 1665-1694, 2014.
  6. [6] Becker C, Scholl A. “A survey on problems and methods in generalized assembly line balancing”. European Journal of Operational Research, 168(3), 694-715, 2006.
  7. [7] Boysen N, Fliedner M, Scholl A. “A classification of assembly line balancing problems”. European Journal of Operational Research, 183(2), 674-693, 2007.
  8. [8] Bartholdi JJ. “Balancing two-sided assembly lines: a case study”. International Journal of Production Research, 31(10), 2447-2461, 1993.

Ayrıntılar

Birincil Dil

İngilizce

Konular

Algoritmalar ve Hesaplama Kuramı , Veri Yapıları ve Algoritmalar

Bölüm

Araştırma Makalesi

Yazarlar

Yayımlanma Tarihi

28 Aralık 2024

Gönderilme Tarihi

4 Ekim 2023

Kabul Tarihi

8 Şubat 2024

Yayımlandığı Sayı

Yıl 2024 Cilt: 30 Sayı: 7

Kaynak Göster

APA
Aslan, Ş. (2024). A hybrid genetic algorithm for solving energy-efficient mixed-model robotic two-sided assembly line balancing problems with sequence-dependent setup times. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, 30(7), 944-956. https://izlik.org/JA42YE88ZC
AMA
1.Aslan Ş. A hybrid genetic algorithm for solving energy-efficient mixed-model robotic two-sided assembly line balancing problems with sequence-dependent setup times. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi. 2024;30(7):944-956. https://izlik.org/JA42YE88ZC
Chicago
Aslan, Şehmus. 2024. “A hybrid genetic algorithm for solving energy-efficient mixed-model robotic two-sided assembly line balancing problems with sequence-dependent setup times”. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi 30 (7): 944-56. https://izlik.org/JA42YE88ZC.
EndNote
Aslan Ş (01 Aralık 2024) A hybrid genetic algorithm for solving energy-efficient mixed-model robotic two-sided assembly line balancing problems with sequence-dependent setup times. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi 30 7 944–956.
IEEE
[1]Ş. Aslan, “A hybrid genetic algorithm for solving energy-efficient mixed-model robotic two-sided assembly line balancing problems with sequence-dependent setup times”, Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, c. 30, sy 7, ss. 944–956, Ara. 2024, [çevrimiçi]. Erişim adresi: https://izlik.org/JA42YE88ZC
ISNAD
Aslan, Şehmus. “A hybrid genetic algorithm for solving energy-efficient mixed-model robotic two-sided assembly line balancing problems with sequence-dependent setup times”. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi 30/7 (01 Aralık 2024): 944-956. https://izlik.org/JA42YE88ZC.
JAMA
1.Aslan Ş. A hybrid genetic algorithm for solving energy-efficient mixed-model robotic two-sided assembly line balancing problems with sequence-dependent setup times. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi. 2024;30:944–956.
MLA
Aslan, Şehmus. “A hybrid genetic algorithm for solving energy-efficient mixed-model robotic two-sided assembly line balancing problems with sequence-dependent setup times”. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, c. 30, sy 7, Aralık 2024, ss. 944-56, https://izlik.org/JA42YE88ZC.
Vancouver
1.Şehmus Aslan. A hybrid genetic algorithm for solving energy-efficient mixed-model robotic two-sided assembly line balancing problems with sequence-dependent setup times. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi [Internet]. 01 Aralık 2024;30(7):944-56. Erişim adresi: https://izlik.org/JA42YE88ZC